PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIAS DA SAÚDE

Associação de polimorfismos no gene

do receptor DRD2 e nos genes das

enzimas MAOA e COMT com a ingestão

alimentar e parâmetros de adiposidade

entre crianças de três a quatro anos de

idade.

Ananda Cristine Santos Galvão

Orientadora: Drª Silvana de Almeida

Co-orientadora: Drª Márcia Regina Vitolo

Dissertação de Mestrado

Patogênese e Fisiopatologia

2010

Livros Grátis

http://www.livrosgratis.com.br

Milhares de livros grátis para download.

Programa de Pós-Graduação em Ciências da Saúde

Associação de polimorfismos no gene

do receptor DRD2 e nos genes das

enzimas MAOA e COMT com a ingestão

alimentar e parâmetros de adiposidade

entre crianças de três a quatro anos de

idade.

Ananda Cristine Santos Galvão

Orientadora: Drª Silvana de Almeida

Co-orientadora: Drª Márcia Regina Vitolo

Dissertação de Mestrado

Patogênese e Fisiopatologia

2010

G182a Galvão, Ananda Cristine Santos

Associação de polimorfismos no gene do receptor DRD2 e nos genes das enzimas MAOA e COMT com a ingestão alimentar e parâmetros de adiposidade entre crianças de três a quatro anos de idade / Ananda Cristine

Santos Galvão. Porto Alegre, 2010. 119 f. : il.

Dissertação (Mestrado) – Programa de Pós-Graduação em

Ciências da Saúde – Universidade Federal de Ciências da Saúde de Porto Alegre, 2010.

Orientador: Silvana Almeida Co-orientador: Márcia Regina Vítolo

1. Obesidade infantil. 2. Ingestão alimentar. 3.Regulação do apetite. 4.

Polimorfismo. 5.Monoaminoxidase. 6.Receptores dopaminérgicos. I. Título. II. Almeida, Silvana. III. Vítolo, Márcia Regina.

CDD 616.852 6

Eleonora Liberato Petzhold CRB10/1801

INSTITUIÇÕES E FONTES FINANCIADORAS

As pesquisas foram realizadas no laboratório de Biologia Molecular do Centro de Pesquisa e Pós-Graduação Heitor Cirne Lima e foram subvencionadas pelo Conselho Nacional de Desenvolvimento Científico e Técnológico (CNPq) – CNPq/Universal processo nº 476/66/2006-3, Programa de Apoio à Pós-Graduação – CAPES (PROAP-CAPES) e Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS) – PPSUS/2006 processo nº 070026-9.

A aluna recebeu bolsa de estudos concedida pela Coordenação de

Aperfeiçoamento de Pessoal de Nível Superior (CAPES).

AGRADECIMENTOS

À minha orientadora, Silvana de Almeida, por toda dedicação, incentivo e

paciência. Por ter acreditado, por estar sempre disposta e, mesmo com um

compromisso tão importante recém chegado (Clarissa), tinha tempo par responder

as minhas inúmeras dúvidas. Obrigada por ser tão presente!

À Grasi e Magda, pela ajuda em todos os momentos e por fazerem o nosso

laboratório funcionar, além de proporcionar excelentes momentos de descontração.

Às meninas do laboratório 203, Lú, Juci, Lisi, Mela, Lila, Lisi 2, Michi, Gabi,

Raquel... Obrigada por terem tornado esta caminhada mais florida e

indiscutivelmente mais alegre!!!

À professora Márcia Vitollo, por ter me acolhido em seu grupo de pesquisas,

cedendo os préstimos valorosos de sua doutoranda Paula Campagnolo, sempre

engrandecendo a parte metodológica do trabalho.

Aos meus pais por servirem sempre como exemplo de perseverança, força e

capacidade inigualável de não se deixar abater por nada, por sempre acreditar na

minha capacidade e assim me fazendo acreditar que realmente sou capaz de seguir

em frente e realizar as coisas a que me proponho. E por todo amor dedicado a mim.

À todos da minha família que, mesmo entendendo pouco do que faço, sempre

me apoiaram e incentivaram, em especial à minha tia Vera por sua constante

colaboração para a minha formação, na parte financeira, na forma de livros

presenteados e ainda como exemplo de determinação.

À minha prima e madrinha, Mirelle Beulke, por ser mais que uma prima, por

ser o meu exemplo de profissional e pessoa e cuja trajetória me incentiva muito a

seguir em frente.

Ao meu namorado, Ricardo, por sempre valorizar todas as coisas que faço,

apoiando-me e incentivando a não abandonar meus sonhos. Obrigada por estar ao

meu lado nessa caminhada, ajudando a superar os desafios que surgiram na minha

vida. Te amo muito, tu és uma pessoa excepcional.

À minha cunhada Rebeca, por ter sido um anjinho que entrou na minha vida

quando eu mais precisei de todos os anjos ao meu favor!!! Você fez toda a

diferença. Te amo “forever and ever”.

Aos tios Ary e Tânia por todo o amor, carinho e incentivo que me foram

ofertados durante toda a minha trajetória. Obrigada por fazer parte da minha vida de

forma tão presente. Adoro vocês.

Ao meu afilhado, Matheus, pelos momentos de alegria e descontração que

tornam a caminhada sempre mais branda. À sua família em especial à Elizabeth, por

toda sua generosidade e amor que me foi dado, além de todo o suporte às vezes até

financeiro e dos deliciosos lanchinhos de madrugada enquanto estudava. Obrigada!

À minha amiga, Rafaela e Paloma por me aturar nos momentos mais

estressantes desde o início desta jornada, e também pelos momentos anteriores a

ela, mas que me fizeram chegar até aqui. Obrigada pela amizade. Vocês são

pessoas muito especiais, amo vocês.

Às amigas e companheiras não mais de estudo, mas de vida, Isa, Michi, Cris,

Fer, Leti e Maria Fer pelas horas de risadas, festas e também pelas horas

desprendimento, ao compartilhar as das minhas dificuldades, sendo meu apoio

incondicional. Vocês moram no meu coração!

Às amigas da terrível fase de pré-vestibular e que me acompanham até hoje,

Lika, Clô, Carol, Vâni, Gyh (você sempre quis estar dentro deste gênero) sem vocês

teria sido muito mais difícil ter começado a vida acadêmica. Vocês são demais!

“Eu creio em mim mesmo e nos que trabalham

comigo, creio nos meus amigos e creio na minha

família. Creio que Deus me emprestará tudo que

necessito para triunfar, contanto que eu me

esforce para alcançar com meios lícitos e

honestos. Creio que o triunfo é resultado de

esforço inteligente que não depende da sorte.

Creio que tirarei da vida exatamente o que nela

colocar. Prestarei o melhor serviço de que sou

capaz, porque sei que o triunfo é sempre

resultado do esforço consciente e eficaz”.

Mahatma Gandhi

ABSTRACT

Place of Origin / Performance: Laboratory of Molecular Biology, Centro de Pesquisa e

Pós-Graduação Heitor Cirne Lima, UFCSPA.

Background: The increased prevalence of obesity in the world is becoming one of the most

important clinical and epidemiological phenomena at present day. Environmental factors

such as changes in lifestyle and feeding behavior associated with poorly characterized

genetic determinants are thought to play the most important roles in the pathogenesis of this

disease. During the last years great advances were obtained in the characterization of the

hypothalamic mechanisms involved in food intake control. Such advances are unveiling a

complex and integrated system. Despite the contribution of genetic factors to the

development of weight gain being widely recognized, the real quantitative contribution of

them is a complex question yet to be answered. Evidence obtained from studies with humans and

animal models indicate the importance of dopaminergic function in the development of obesity for their role in

regulating appetite. Power is associated with the release of dopamine in the dorsal striatum and the degree of

pleasure experienced during food intake is directly related to the amount of dopamine released in this region.

These evidences are divided about the direction of causal association. One argument is that

a Reward Deficiency Syndrome is the risk factor, while others contend that hyper-sensitivity

to reward enhances the motivation for pleasurable activities like eating. The genes of the

dopamine receptor 2 (DRD2), the enzyme monoamine oxidase A (MAOA) and catechol-O-

methyltransferase (COMT), encode proteins that control the availability of these

neurotransmitters and have polymorphisms (TaqIA and-141C Ins/Del - DRD2; MAOA-u

VNTR and T941G - MAOA; Val158Met - COMT), which alter their activity and expression.

The variants of these genes may be associated with differential intake of food in their

carriers. Whereas the prevalence of obese children has increased in recent decades, and

obesity increases the risk for various diseases, the identification of individuals who are

genetically more susceptible could be important for the prevention and / or treatment of

obesity.

Objectives: To investigate the association of variants TaqIA and -141C Ins/Del of

dopamine receptor 2 gene (DRD2); variant MAOA-u VNTR and T941G of monoamine

oxidase A gene (MAOA) and Val158Met variant of the gene for catechol-O -

methyltransferase (COMT) in the regulation of body weight and the aspects related to

obesity and food consumption.

Material and Methods: We conducted a cross-sectional study aligned to a randomized

clinical trial. DNA was extracted from blood samples of 354 children, polymorphisms DRD2

TaqIA, DRD2 -141C Ins / Del, MAOA T941G and COMT Val158Met were amplified by PCR

and further subjected to cleavage with restriction endonuclease, the genotypes were

visualized after gel electrophoresis agarose and acrylamide (COMT Val158Met); The

fragment containing the MAOA-u VNTR polymorphism was analyzed by PCR followed by

electrophoresis on acrylamide gels.

Results and Conclusions: The distributions of genotype frequencies found are in

agreement with the expected under Hardy-Weinberg equilibrium. Regarding the

polymorphism DRD2 -141C Ins / Del and MAOA T941G there were no statistically

significant differences regarding the intake of foods with high sugar density (HSD) and high

lipid density (HLD), total caloric intake, the BMI Z score, the percentile skinfolds and waist

circumference among patients of different genotypes. For DRD2 TaqIA polymorphism, the

sample was divided into whites and non-whites. Children of the sample of non-whites with

genotype TaqIA C/C had a higher intake of HLD (159.4 kcal [44.26-272.34]) compared with

children with the T allele (82.2 kcal [0.00-195.01], p = 0.009). To analyze the polymorphisms

in the MAOA gene, the sample was divided into boys and girls. In the sample of boys, the

MAOA-u*long allele was associated with higher consumption of HLD (134.975kcal [26437-

270162]) when compared to MAOA-u*short allele (60.1kcal [0.000-192.31], p = 0.009). The

consumption of HSD was also higher in boys with the MAOA-u*long allele (100.455kcal

[54406-163325]) compared to carriers of MAOA-u*short allele (80.015kcal [37.45-127.115],

p = 0.034). In the sample of girls, the MAOA-u VNTR polymorphism was not associated with

food intake and anthropometric data. COMT Val158Met polymorphism in the carriers

COMT*158Val allele had a higher consumption of HLD compared with homozygous for the

COMT*158Met allele (p = 0.008), the medians were 133.79kcal [44.23-265.80] and

83.37Kcal [0.00-252.95] respectively. These findings indicate the association of

polymorphisms in DRD2, MAOA and COMT in the regulation of food intake and as a

potential risk factor for obesity.

Keywords: DRD2, MAOA and COMT polymorphisms; food intake; children obesity

RESUMO

Local de Origem/Realização: Laboratório de Biologia Molecular, Centro de Pesquisa e

Pós-Graduação Heitor Cirne Lima, UFCSPA.

Introdução: O aumento da prevalência de obesidade em todo o mundo vem se

revelando como um dos mais importantes fenômenos clínico-epidemiológicos da

atualidade. Fatores como a mudança do hábito alimentar e o estilo de vida sedentário,

aliados a determinantes genéticos ainda pouco conhecidos, desempenham um papel

relevante na patogênese desta doença. Nos últimos anos avanços consideráveis foram

obtidos na caracterização dos mecanismos hipotalâmicos do controle da ingestão

alimentar. Tais avanços têm revelado as particularidades de um sistema complexo e

integrado. Apesar da contribuição de fatores genéticos no desenvolvimento do ganho de

peso ser amplamente reconhecida, a real contribuição quantitativa dos mesmos em

fenótipos relacionados é ainda uma questão complexa que precisa ser elucidada.

Evidências obtidas, a partir de estudos com humanos e modelos animais, indicam a

importância da função dopaminérgica no desenvolvimento da obesidade por seu papel

na regulação do apetite. A alimentação está associada com a liberação de dopamina no

estriado dorsal e o grau de prazer sentido durante a ingestão alimentar está diretamente

associado à quantidade de dopamina liberada nessa região. Essas evidências estão divididas

sobre a direção da causa da associação. Um argumento é que a Síndrome de Deficiência da Recompensa

é um fator de risco, enquanto outros afirmam que hiper-sensibilidade à recompensa aumenta a motivação

para atividades prazerosas como comer. Os genes do receptor dopaminérgico 2 (DRD2), das

enzimas monoaminoxidase-A (MAOA) e catecol-O-metiltransferase (COMT), codificam

proteínas que controlam a disponibilidade destes neurotransmissores e possuem

polimorfismos (TaqIA e -141C Ins/Del – DRD2; MAOA-u VNTR e T941G – MAOA;

Val158Met - COMT), que alteram as suas atividades e expressão. As variantes destes

genes podem estar associadas com ingestão diferencial de alimentos em seus

portadores. Considerando que a prevalência de crianças obesas tem aumentado nas

últimas décadas e a obesidade aumenta o risco para diversas doenças, a identificação

dos indivíduos que são geneticamente mais susceptíveis pode ser importante para a

prevenção e/ou no tratamento da obesidade.

Objetivos: Investigar a associação das variantes TaqIA e -141C Ins/Del do gene do

receptor de dopamina 2 (DRD2); variante MAOA-u VNTR e T941G do gene da

monoaminooxidase A (MAOA); e variante Val158Met do gene da catecol-O-

metiltransferase (COMT) na regulação do peso corporal e os aspectos relacionados à

obesidade e consumo alimentar.

Material e Métodos: Foi realizado um estudo transversal alinhado a um ensaio clínico

randomizado. O DNA foi extraído de amostras de sangue de 354 crianças, os

polimorfismos DRD2 TaqIA, DRD2 -141C Ins/Del, MAOA T941G e COMT Val158Met

foram amplificados por PCR e após submetidos a clivagem com endonuclease de

restrição, os genótipos foram visualizados posteriormente a eletroforese em gel de

agarose e acrilamida (COMT Val158Met); O fragmento contendo o polimorfismo MAOA-

u VNTR foi analisado por PCR seguida de eletroforese em gel de acrilamida.

Resultados e Conclusões: As distribuições das frequências genotípicas encontradas

estão de acordo com o esperado sob equilíbrio de Hardy-Weinberg. Com relação ao

polimorfismo DRD2 -141C Ins/Del e MAOA T941G não foram encontradas diferenças

estatisticamente significantes quanto à ingestão de alimentos com alta densidade de

açúcar (HSD) e alta densidade de gordura (HLD), ingestão calórica total, ao escore Z do

IMC, ao percentil de dobras cutâneas e a circunferência da cintura entre os portadores

dos diferentes genótipos. Para o polimorfismo DRD2 TaqIA, a amostra foi separada em

indivíduos brancos e não-brancos. As crianças da amostra de não-brancos com o

genótipo TaqIA C/C apresentaram maior ingestão de HLD (159.4 kcal [44.26–272.34])

quando comparadas com crianças portadoras do alelo T (82.2 kcal [0.00–195.01],

p=0.009). Para analisar os polimorfismos no gene da MAOA a amostra foi dividida em

meninos e meninas. Na amostra de meninos, o alelo MAOA-u*longo foi associado com

maior consumo de HLD (134.975kcal [26.437–270.162]) quando comparado ao MAOA-

u*curto (60.1kcal [0.000–192.31]; p = 0.009). O consumo de HSD também foi maior em

meninos portadores do alelo MAOA-u*longo (100.455kcal [54.406–163.325]) quando

comparados aos portadores do alelo MAOA-u*curto (80.015kcal [37.45–127.115]; p =

0.034). Na amostra de meninas, o polimorfismo MAOA-u VNTR não foi associado com a

ingestão alimentar e dados antropométricos. No polimorfismo COMT Val158Met os

portadores do alelo COMT*158Val tiveram um consumo maior de HLD em comparação

aos homozigotos para o alelo COMT*158Met (p = 0.008), as medianas foram 133.79kcal

[44.23–265.80] e 83.37Kcal [0.00–252.95], respectivamente. Estes achados indicam a

associação destes polimorfismos nos genes DRD2, MAOA e COMT com a regulação da

ingestão alimentar e como fator de risco potencial para obesidade.

Palavras-chave: Polimorfismos em DRD2, MAOA e COMT; consumo alimentar; obesidade infantil.

SUMÁRIO

CAPÍTULO 1

INTRODUÇÃO ...................................................................................................... 14

1.1 Obesidade ............................................................................................................. 15

1.1.1 Comportamento Alimentar ............................................................................ 15

1.2 Fatores Genéticos ................................................................................................ 18

1.3 Sistema Dopaminérgico ....................................................................................... 19

1.4 Receptores de Dopamina – Gene DRD2 ................................................................. 22

1.4.1 Polimorfismo TaqIA ....................................................................................... 23

1.4.2 Polimorfismo -141C Ins/Del ........................................................................... 25

1.5 Monoaminooxidases – Gene MAOA ...................................................................... 26

1.5.1 Polimorfismo MAOA-u VNTR .......................................................................... 27

1.5.2 Polimorfismo MAOA T941G ............................................................................ 29

1.6 Catecol--metiltransferase – Gene COMT .............................................................. 29

1.6.1 Polimorfismo COMT Val158Met ...................................................................... 30

JUSTIFICATIVA ----------------------------------------------------------------------------------- 32

OBJETIVOS ---------------------------------------------------------------------------------------- 33 CAPÍTULO 2

REFERÊNCIAS BIBLIOGRÁFICAS --------------------------------------------------------- 34

CAPÍTULO 3

MANUSCRITO 1 ---------------------------------------------------------------------------------- 42

CAPÍTULO 4

MANUSCRITO 2 ---------------------------------------------------------------------------------- 61

CAPÍTULO 5

ANEXOS -------------------------------------------------------------------------------------------- 89

CAPÍTULO 1

INTRODUÇÃO

16

1.1 Obesidade A obesidade é um fator de risco para múltiplos problemas de saúde nos adultos, entre

estes problemas destacam-se a doença cardíaca, a aterosclerose, a elevação do colesterol, a

pressão sanguínea elevada, determinados tipos de cânceres e diabetes (LEWIS & MAN, 2007).

Em um estudo epidemiológico, no qual foi examinada a variação de peso de crianças e

adolescentes detectou-se que a partir dos três anos de idade o excesso de peso torna-se

definitivamente determinante de obesidade futura; e que se a criança é obesa aos seis anos de

idade ela apresenta 50% de chance de tornar-se um adulto obeso (MORAN, 1999). Dados de

pesquisas populacionais brasileiras mostram que a prevalência de obesidade em crianças de seis

a nove anos triplicou entre 1974 e 1997 (WANG et al., 2002a). O excesso de peso como problema

de saúde pública tornou-se mais prevalente que a desnutrição no Brasil e no restante do mundo

(POPKIN et al., 2001). A epidemia recente de obesidade infantil despertou interesse no seu estudo

em função das conseqüências possíveis sobre a saúde clínica e pública (REILLY et al., 2003). O

que se pode presumir é que estas terão impacto considerável no futuro sobre custos e serviços de

saúde tornando-os mais onerosos (MOZAFFARI & NABAEI, 2007). O desenvolvimento de

obesidade resulta de um conjunto de fatores comportamentais e ambientais que conduzem ao

balanço energético positivo.

1.1.1 – Comportamento alimentar

O comportamento alimentar envolve o apetite (sensação de fome e saciedade), os estados

motivacionais e a necessidade de ingestão energética (processos fisiológicos e metabólicos),

coordenados pela atividade dos sistemas nervosos periférico e central (vias neurais e receptores)

(NETTO, 1998) É consenso que modificações no comportamento alimentar se impõem para

prevenir doenças relacionadas à alimentação e promover a saúde do indivíduo. Uma vez que é na

17

infância que o hábito alimentar se forma, é necessário o entendimento dos seus fatores

determinantes (ANGELIS, 1995; SPLETT, 1991). A literatura sobre nutrição infantil evidencia que o

comportamento alimentar do pré-escolar é determinado em primeira instância pela família, da qual

ela é dependente e, secundariamente, pelas outras interações psicossociais e culturais da criança

(BIRCH, 1998; ROZIN, 1997). O padrão da alimentação do pré-escolar é determinado por suas

preferências alimentares. A dificuldade é fazer com que a criança aceite uma alimentação variada,

aumentando suas preferências e adquirindo um hábito alimentar mais adequado (KOIVISTO &

SJÖDÉN, 1996). A aprendizagem é central no desenvolvimento do padrão alimentar da criança

(BIRCH, 1997). Entende-se hábito como sendo um ato, uso e costume, ou um padrão de reação

adquirido por freqüente repetição da atividade (aprendizagem). Esse termo também pode ser

aplicado, por generalização, a normas de comportamento (FERREIRA, 2004; CABRAL, 1974).

Assim, os alimentos ou tipo de alimentação que os indivíduos consomem rotineiramente e

repetidamente no seu cotidiano caracterizam o seu hábito ou comportamento alimentar. No

entanto, não é simplesmente a repetição do consumo do alimento que desenvolve o

comportamento alimentar. Existe um grande número de fatores inter-relacionados, de origem

interna e externa ao organismo, que influenciam a aquisição desse comportamento. Cabe

ressaltar que o hábito alimentar não necessariamente é sinônimo das preferências alimentares do

indivíduo. Porém, no caso específico dos pré-escolares, o hábito alimentar caracteriza-se

fundamentalmente pelas suas preferências alimentares. As crianças desta faixa etária acabam

consumindo somente alimentos de que gostam, entre os disponíveis no seu ambiente, refutando

aqueles de que não gostam (BIRCH, 1998; ROZIN, 1997). Os fatores psicossociais influenciam as

experiências alimentares desde o momento do nascimento da criança, proporcionando a

aprendizagem inicial para a sensação da fome e da saciedade e para a percepção dos sabores. A

adequada introdução dos novos alimentos no primeiro ano de vida, com uma correta socialização

18

alimentar, a partir deste período, bem como a disponibilização de variados alimentos saudáveis

em ambiente alimentar agradável, permite à criança iniciar a aquisição das preferências

alimentares responsáveis pela determinação do seu padrão de consumo (BIRCH, 1998). A

tendência das preferências alimentares das crianças na idade pré-escolar conduz ao consumo de

alimentos com quantidade elevada de carboidrato, açúcar, gordura e sal, e baixo consumo de

alimentos como vegetais e frutas, se comparados às quantidades recomendadas (KREBS-SMITH

et al., 1996). Esta tendência é originada na socialização alimentar da criança e depende, em

grande parte, dos padrões da cultura alimentar do grupo social ao qual ela pertence. A

sensibilidade ao sabor doce já aparece na fase pré-natal, sendo, portanto, uma preferência inata.

Possivelmente, devido a esta sensibilidade ao doce estimulada pelas substâncias químicas do

líquido amniótico durante a fase pré-natal (BEAUCHAMP & MENNELLA, 1994), verifica-se um

aumento da aceitação de alimentos desconhecidos, quando estes estão associados ao açúcar ou

a alimentos naturalmente adocicados. Neste tipo de aprendizagem, o sabor está associado ao

prazer e provavelmente por esta razão se mantém ao longo do tempo, ou seja, é durável e sua

modificação só é possível quando outra experiência aprendida substitua ou neutralize a

experiência anterior (CAPALDI, 1997). Por este motivo observa-se que a preferência por consumo

de alimentos ricos em açúcar e gordura pode levar o indivíduo a obesidade na idade adulta.

Segundo MARTI & MARTINEZ (2006) o risco de obesidade, na prática, depende pelo

menos de dois fatores importantes, que interagem mutuamente: 1) as variantes e a expressão

genética e 2) a exposição aos fatores de risco ambientais. Quando existe predisposição genética

para o desenvolvimento da obesidade, o ambiente e o estilo de vida do indivíduo potencializam o

seu desenvolvimento. Portanto, as diferenças genéticas podem esclarecer algumas das

discrepâncias encontradas no ganho de peso entre populações, entretanto, a prevalência da

obesidade na sociedade deve refletir também mudanças no estilo de vida (hábitos, sedentarismo,

19

etc.), já que a predisposição genética pode ser influenciada por mudanças na exposição

ambiental.

1.2 Fatores Genéticos

Muitos genes têm sido investigados pelo seu provável papel na determinação da

composição corporal (RANKINEN et al., 2006). Os genes candidatos para estudo são os que

codificam proteínas relacionadas às diferentes vias metabólicas, como a regulação do apetite,

sensibilidade à insulina e diferenciação de adipócitos, e as envolvidas na termogênese, no

catabolismo e transporte de ácidos graxos (MALCZEWSKA-MALEC et al., 2004). Uma das linhas

muito pouco investigadas na avaliação do componente genético da obesidade é o estudo de

variantes dos genes relacionados ao comportamento de ingestão alimentar de adultos e crianças.

Grandes avanços têm sido alcançados no campo da genética das doenças multifatoriais,

tais como obesidade, cardiopatias, diabetes e câncer. A evidência de associações entre genes

candidatos e fenótipos relacionados à obesidade passam de 127 genes em que foram

encontradas associações significativas (RANKINEN et al., 2006). A conclusão do Projeto Genoma

Humano (INTERNATIONAL HUMAN GENOME SEQUENCING CONSORTIUM, 2001) é

considerada um importante passo no objetivo de revelar as bases genéticas de doenças

complexas (HUMPHRIES & ORDOVAS, 2001). Variações em um grande número de genes

envolvidos na síntese de proteínas estruturais e enzimas relacionadas no metabolismo de

neurotransmissores envolvidos com o consumo alimentar poderiam, a princípio, responder por

variações de comportamento alimentar de cada indivíduo. Desta maneira, qualquer gene que seja

responsável pela produção de uma proteína envolvida nesta rota metabólica poderia ser um “gene

candidato” na investigação de determinantes genéticos da obesidade. Assim, o somatório de

20

variações com pequeno efeito em cada um destes genes poderia levar à alteração do

comportamento alimentar de um indivíduo, predispondo à obesidade.

Como estas variantes genéticas são bastante freqüentes na população em geral (de 1% a

80% dos indivíduos), seu impacto é muito maior na saúde pública quando comparadas com

mutações de grande efeito, mas que são muito mais raras. Estas variações quando são

freqüentes são chamadas polimorfismos (mais de 1% de freqüência do alelo mais raro). A base

genética para esta variação pode ser uma troca de bases no DNA, uma duplicação ou deleção de

um ou vários pares de bases. Estimativas atuais sugerem que variações de uma única base entre

indivíduos (single nucleotide polymorphisms, ou SNPs) ocorrem na freqüência de um SNP a cada

1.300pb, ou seja, existem mais de 1.4 milhão de polimorfismos de substituição de uma única base

em nosso genoma (INTERNATIONAL HUMAN GENOME SEQUENCING CONSORTIUM, 2001).

O estudo da associação de variações no DNA com suscetibilidade a certas doenças ou

características é uma área promissora da genética. Investigações nesta área podem ser

realizadas basicamente de duas maneiras: (1) avaliando-se a distribuição da frequência alélica e

genotípica entre grupos de indivíduos portadores de uma determinada doença ou característica,

como obesidade, por exemplo; (2) analisando-se as médias de parâmetros, relacionados com a

característica ou a patologia, entre os grupos de indivíduos portadores dos diferentes genótipos.

1.3 Sistema Dopaminérgico

Existem diversos aspectos a serem considerados na regulação do comportamento

alimentar. Dentre os aspectos qualitativos do controle de apetite, podemos citar os mecanismos

relacionados à seleção de certos nutrientes específicos ou grupos de nutrientes, os quais são

determinados pelo grau de prazer experimentado pelos indivíduos (sistema mesolímbico de

21

recompensa). Neste contexto, a dopamina, um neurotransmissor endógeno, é especialmente

interessante, pois, além de modular uma variedade de funções fisiológicas, como o transporte

iônico, o tônus vascular e a pressão sanguínea, possui um papel principal na regulação do apetite

(FANG et a.l, 2005). Evidências obtidas, a partir de estudos com humanos e modelos animais,

indicam a importância da função dopaminérgica no desenvolvimento da obesidade por seu papel

na regulação do apetite (SCHACHTER et al., 1968). Em humanos, a obesidade foi associada com

uma ação anormal da dopamina no cérebro (NOBLE, 2000a).

Quando baixa o nível de dopamina nos neurônios pós-sinápticos da via mesolímbica quer

por diminuição da produção desse neurotransmissor, quer por redução do numero de seus

receptores D2, as mesmas condições que antes atuavam como autênticos estímulos naturais já

não se mostram suficientes para gerar sensações prazerosas ou de bem estar. O indivíduo passa,

então, a buscar, através de alterações comportamentais, o aumento da liberação de dopamina

para o sistema límbico. Nesse caso incluem-se o uso e abuso de substâncias químicas, como

álcool, cafeína, que parecem induzir o aumento da liberação de dopamina, assim como aumento

do consumo alimentar, levando assim a um aumento da obesidade entre esses indivíduos

(OLIVEIRA, 1999). FANG et al., (2005) demonstraram que drogas agonistas do sistema

dopaminérgico são capazes de suprimir o apetite e, subseqüentemente, reduzir o peso. A

participação do sistema dopaminérgico na recompensa e no reforço, após a ingestão alimentar,

conduziu à hipótese de que há baixa atividade de dopamina no cérebro em pacientes obesos e

pacientes pré-dispostos ao consumo excessivo de alimentos (WANG et al., 2002b). BLUM et al.,

(2007), sugeriram que um fator genético, ainda desconhecido, agiria sobre a atividade

dopaminérgica no centro da recompensa do cérebro influenciando o comportamento -

aumentando o desejo de consumir doces e tendo como conseqüência a obesidade. Este defeito

estimula os indivíduos para encontrar nos excessos (alimentares ou entorpecentes) um aumento

22

da função da dopamina no cérebro, categorizando o que foi denominado de Síndrome da

Deficiência da Recompensa (RDS). Atualmente considera-se que o alimento poderia ser o mais

importante estimulador natural do sistema de recompensa no cérebro (EPSTEIN & LEDDY, 2006).

Portanto, comer em excesso pode representar uma tentativa de compensar a deficiência de

recompensa em condições de atividade dopaminérgica reduzida. A deficiência dopaminérgica

relativa pode ser causada por diferentes condições, por exemplo, a predisposição genética ou

após regulação negativa adaptativa do sistema dopaminérgico, devido à hiperestimulação anterior.

Um efeito rebote do comportamento alimentar após hiperestimulação dopaminérgica poderia

explicar o ganho de peso, muitas vezes associados a cessação do tabagismo, porque durante o

fumo, a nicotina estimula células que contém dopamina, na área ventral tegmental, resultando na

liberação desta dopamina nas projeções mesolímbica e mesocortical (KAUER, 2005). Além disso,

o aumento de peso é um efeito colateral de muitas drogas comumente usadas. Até a data, os

mecanismos subjacentes são ainda mal compreendidos, embora as interações com o sistema de

dopamina já tenham sido implicadas (GOUDIE et al., 2003). Outro mecanismo de ação proposto

sobre a influência do sistema dopaminérgico sobre o comportamento alimentar, caminha na

direção contrária e afirma que uma hiper-sensibilidade à recompensa aumentaria a motivação

para atividades prazerosas como comer. Em vários estudos, a elevada sensibilidade à

recompensa contribui para o aumento do risco de desenvolvimento de comportamentos aditivos

para abordagem de atividades potencialmente prazerosa tais como o consumo de drogas e

comer, tendo sido inclusive associado à preferência por alimentos ricos em gordura, compulsão

alimentar, e ânsia pelo alimento, bem como com o consumo perigoso de álcool (DAVIS et al.,

2004, 2007; DAVIS & WOODSIDE, 2002; FRANKEN & MURIS, 2005; LOXTON & DAWE, 2001,

2006).

23

O sistema dopaminérgico no cérebro possui três principais vias de transmissão –

nigroestriatais, mesocorticais e mesolímbicas. A via nigroestriatal projeta-se da A9 na Substância

Nigra Pars compacta (SNc) do mesencéfalo para o estriado dorsal, em particular, núcleos caudado

e putâmem e está envolvida no controle motor. Manifestações da doença de Parkinson são

atribuídas à redução de entrada dopaminérgica no estriado devido à degeneração de neurônios

dopaminérgicos da SNc (WEINER, 2000). A via mesocortical tem sua origem em corpos celulares

da Área Tegmental Ventral (VTA). Seus axônios enviam projeções excitatórias para o córtex pré-

frontal afetando funções com a formação de memórias de curto prazo, motivação, atenção e

planejamento de estratégia para solução de problemas. Os corpos celulares dos neurônios do

sistema mesolímbico estão também localizados na VTA (A8 e A10). Estas células projetam-se

para várias partes do sistema límbico, incluindo o núcleo accumbens, a amígdala, o hipocampo, o

córtex cingulado e o córtex entorrinal. O núcleo accumbens tem um importante papel nos efeitos

reforçadores de certos tipos de estímulos e nos comportamentos orientados a metas (goal-

directed). Assim, os neurônios dopaminérgicos mesolímbicos estão envolvidos com as

propriedades reforçadoras de várias drogas de abuso, incluindo os psicoestimulantes tais como,

cocaína e anfetamina (VOLKOW et al., 2002) e também com consumo alimentar exagerado, como

citado anteriormente.

1.4 Receptores de Dopamina – Gene DRD2 Além das diferenças anatômicas, existem também diferenças funcionais entre essas vias,

demonstrando a heterogeneidade da população de neurônios cuja dopamina é neurotransmissor.

Nessas células, cinco subtipos de receptores dopaminérgicos foram encontrados: DRD1 – DRD5

(SEEMAN et al. 1993). Estes receptores são divididos em duas subfamílias, DRD1-like (DRD1 e

24

DRD5) cuja ação intracelular é ativar a adenil-ciclase, a qual catalisa a formação de AMPc, que por

sua vez ativa a proteína quinase A (PKA) regulando canais iônicos e fatores de transcrição; e

DRD2-like (DRD2, DRD3 e DRD4) que inibe a adenil-ciclase e ativa os canais de K+.

O gene que codifica o receptor de dopamina D2 (DRD2) foi mapeado por Grandy em 1989

no cromossomo 11 (q22-q23), sendo a sua seqüência codificadora interrompida por seis introns,

originando uma proteína com sete domínios transmembrana (NOBLE, 2000b). WANG et al. (2007)

em seu estudo demonstraram que a obesidade e o índice de massa corporal estão

correlacionados negativamente com a densidade de receptores D2 no estriato (WANG et al.,

2001; HALTIA et al., 2007), o que pode refletir uma neuroadaptação secundária a

superestimulação com alimentos palatáveis (COLANTUONI et al., 2001; BELLO et al., 2002).

Assim, o aumento da ingestão de alimentos pode ser um comportamento compensatório para a

baixa quantidade de receptores dopaminérgicos (DAVIS et al., 2004). Está bem estabelecido que

a alimentação está associada com a liberação de dopamina no estriado dorsal e que o grau de

prazer sentido durante a ingestão alimentar está diretamente associado à quantidade de dopamina

liberada nessa região. No entanto, essas evidências estão divididas sobre a direção da causa da

associação. Um dos argumentos é que a Síndrome de Deficiência da Recompensa é um fator de

risco para o comer compulsivo, enquanto que outros afirmam que hiper-sensibilidade à

recompensa aumenta a motivação para atividades prazerosas como comer.

1.4.1 Polimorfismo TaqIA

STICE et al. (2008) descreveu recentemente menor ativação estriatal em resposta à

ingestão de alimentos em indivíduos obesos. Além disso, esta relação foi modulada pela

disponibilidade do receptor D2 geneticamente determinada pelo polimorfismo TaqIA (STICE et al.,

25

2008). Os dados transversais e prospectivos obtidos a partir de dois estudos de ressonância

magnética funcional dão suporte às hipóteses de que a alimentação está associada com a

liberação de dopamina no estriato dorsal, e o grau de prazer de comer se correlaciona com a

quantidade de dopamina liberada, o que indicaria que os indivíduos podem comer demais para

compensar um hipofuncionamento no estriato dorsal, particularmente àqueles com variantes

genéticas que atenuam a sinalização de dopamina na região (SMALL et al., 2003; SZCZYPKA et

al., 2001). O gene DRD2 é altamente polimórfico, mas muita atenção foi focalizada no

polimorfismo denominado Taq1A (C32806T ou RS1800497), substituição de C>T situada a 10Kb

da posição 3’ do gene, uma região não codificadora, o qual parece afetar a disponibilidade do

receptor D2 (MUNAFO et al., 2005). O alelo C resulta em um sítio de restrição para a enzima TaqI;

o alelo T que não gera este sítio de restrição era descrito anteriormente como alelo A1. NOBLE et

al. (1994), encontraram associação entre o alelo T e tempo de latência aumentado para as ondas

cerebrais P300 (que estão ligadas à atenção) em filhos de dependentes de álcool, indicando que

variações na função dopaminérgica podem ser herdadas. NOBLE (1997), ao analisar sujeitos sem

diagnóstico de abuso de álcool ou drogas, detectou que o metabolismo cerebral de glicose está

reduzido em portadores do alelo T nas áreas envolvidas no sistema de recompensa cerebral,

como nucleus accumbens, ou reguladoras de função frontal, como córtex pré-frontal.

POHIALAINEN et al. (1998), estudando voluntários saudáveis em uma população finlandesa,

também encontraram associação entre o alelo T e baixa disponibilidade de receptores D2. Em um

estudo sobre hiperprolactinemia induzida pela medicação antipsicótica antagonista do receptor de

dopamina D2, observou-se que os pacientes com o alelo T que recebem medicação antipsicótica

tiveram níveis mais elevados de prolactina e este alelo foi altamente predominante entre aqueles

com hiperprolactinemia (YOUNG et al., 2004). LAWFORD et al. (2003) em um estudo sobre o

tratamento do estresse pós-traumático (PTSD), mostrou que pacientes portadores do alelo T

26

(genótipo T/C), comparados aos indivíduos não portadores deste alelo (genótipo C/C),

apresentaram mais problemas psicopatológicos e maior prevalência de ansiedade/insônia,

disfunção social e depressão.

MORTON et al. (2006) demonstraram que esta variação genética no gene DRD2 modifica

as características sobre o ato de fumar e também sobre a obesidade recompensa-motivada. Em

2007, EPSTEIN et al. observaram em seu estudo que o reforço alimentar foi maior nos obesos do

que em indivíduos não obesos, especialmente em indivíduos obesos com o alelo T. O consumo

de energia foi maior para indivíduos com alto reforço alimentar e maior ainda naqueles com alto

reforço alimentar e com o alelo T (EPSTEIN et al., 2007). Em um estudo realizado por NISOLI et

al. (2009) confirmam que a presença do alelo T não está simplesmente relacionado com o peso

corporal, mas que ele pode ser um marcador de uma condição genética em pessoas com alto

risco de desenvolver comportamento alimentar patológico. Em outro estudo, que avaliou

subgrupos de pessoas obesas, observou-se associação entre ausência do alelo T do polimorfismo

DRD2 TaqIA1 e indivíduos obesos que apresentavam transtorno de compulsão alimentar

periódica (TCAP) (DAVIS et al., 2009). Estes resultados contraditórios demonstram a necessidade

de estudos que demonstrem relação de casualidade entre o alelo T e comportamentos

alimentares que predispõem a obesidade. Além de que, o que se observa é que estes estudos na

grande maioria foram realizados em brancos e já foi verificado que há diferença significativa entre

a freqüência do polimorfismo entre as diversas etnias como demonstrado por DAVIS et col. (2009).

1.4.2 Polimorfismo -141C Ins/Del

Outro polimorfismo, no gene de DRD2, que vem sendo estudado é o -141C Ins/Del

(RS1799732) que corresponde a uma variante genética caracterizada pela presença (Insertion) ou

27

ausência (Deletion) da base nitrogenada citosina (C) na posição 141 da região promotora do

DRD2 (PARSONS et al., 2007). Este polimorfismo já foi associado à diminuição média de 68% da

expressão de receptores D2 (ARINAMI et al., 1997) e também a redução estriatal destes

receptores (JÖNSSON et al., 1999). ARINAMI (1997) encontrou associação entre o alelo -

141C*Ins e susceptibilidade ao desenvolvimento de esquizofrenia que é caracterizada pelo

aumento da disponibilidade de dopamina. Outros estudos que se seguiram também encontraram

associação entre o alelo -141C*Ins e esquizofrenia (OHARA et al., 1998; SCHINDLER et al.,

2002). Já um estudo que avaliou a influência do polimorfimo -141-C Ins/Del sobre a eficácia de

medicação ansiolítica para pacientes depressivos, constatou uma resposta melhor à medicação

nos pacientes que não portavam o alelo -141-C*Del, (SUZUKI et al., 2001). Acredita-se que estes

resultados opostos se devam à possibilidade da freqüência alélica desse polimorfismo variar de

acordo com o grupo étnico. A maioria dos estudos realizados com os polimorfimos no gene que

codifica os receptores de dopamina 2 (DRD2) estão relacionados a distúrbios psiquiátricos. Até o

momento é de nosso conhecimento apenas um estudo que avaliou associação entre o

polimorfismo -141C Ins/Del e comportamento alimentar, e este estudo realizado por DAVIS et col.

(2009), não encontrou associação entre portadores do alelo Del com TCAP.

1.5 Monoaminooxidases – Gene MAOA

As monoaminooxidases (MAO) são enzimas que catalisam a desaminação oxidativa de

monoaminas naturais, entre elas a serotonina, a adrenalina, a noradrenalina e a dopamina

(WEYLER et al., 1990), o que sugere importante papel na manutenção da homeostase destes

neurotransmissores (CHEN, 2004). São flavoenzimas localizadas nas membranas mitocondriais,

nos terminais nervosos, no fígado e em outros órgãos. Os subtipos MAOA e MAOB podem ser

28

distinguidos de acordo com suas propriedades: peso molecular, afinidade pelo substrato e

propriedades imunológicas. Estas enzimas são expressas em todo corpo, mas diferem em

expressão e em seu desenvolvimento em células específicas. A enzima MAOA é expressa em

níveis mais altos em neurônios catecolaminérgicos (FOWLER et al., 1987; THORPE et al., 1987).

MAOA preferencialmente oxida as aminas biogênicas como a serotonina, a noradrenalina e a

epinefrina. Dopamina, tiramina e triptamina são substratos comuns para ambas as formas (CHIBA

et al., 1984). Posteriormente os genes que codificam esses subtipos foram clonados e descobriu-

se que as seqüências de aminoácidos de suas estruturas protéicas apresentam 70% de

homologia (LIONEL, 1995), além de ter uma organização gênica (número de éxons e introns)

idêntica (GRIMSBY et al., 1991). EKLUND et al. (2005) relatou em seu estudo que a dificuldade

de atenção foi associado com baixa atividade de MAO. Os baixos níveis de atividade de MAO

foram associados com desatenção e impulsividade em meninos com TDAH (SHEKIM et al., 1986).

A administração de substâncias que inibem atividade da MAO tem demonstrado significativa

melhora do humor e da ansiedade. Estas provas fisiológicas e farmacológicas tornam o gene da

monoamina oxidase A um candidato para um estudo de associação com ansiedade e ingestão

alimentar.

1.5.1 Polimorfismo MAOA-u VNTR

O gene MAOA está localizado no cromossomo X (p11.23 - p11.4) e é composto por 15

exons e 14 introns. Este gene possui diversos polimorfismos, entre eles um polimorfismo de

número variável de repetições em tandem (MAOA-u VNTR) com unidade de repetição de 30pb,

localizado na região promotora que influencia a expressão do gene; sendo que os alelos com 3,5 e

4 repetições induzem uma transcrição de 2 até 10 vezes mais eficiente que o alelo com 3

29

repetições (DENNEY et al., 1999). Alguns estudos foram discordantes com relação ao alelo raro

de 5 repetições: SABOL et al. (1998) e DECKERT et al. (1999) relataram baixa e alta atividade

transcrição, respectivamente. Os alelos de 3,5 e 4 repetições também foram associados com

maiores níveis de degradação de dopamina e serotonina no líquido cerebroespinal em mulheres

saudáveis (JÖNSSON et al., 2003).

Um estudo observou interação entre MAOA e a variante T do polimorfismo Taq1A do gene

DRD2 com ansiedade e dependência de álcool (ANS / DEP ALC), assim variantes no gene de

MAOA podem modificar a associação entre as variantes de DRD2 e fenótipo ANS / DEP ALC

(HUANG et al., 2007). Também foi encontrada associação entre o alelo MAOA-u*3 e Transtorno

de déficit de atenção e hiperatividade (TDAH) em uma população de Taiwan (XU et al., 2007). KIM

et al. (2006) descreveu uma associação entre variantes da MAOA e relato de dor máxima no pós-

operatório. Um estudo que avaliou genes envolvidos com o funcionamento do sistema

serotoninérgico e dopaminérgico encontrou associação entre o polimorfismo MAOA-u VNTR e a

predição das categorias de IMC observando que o alelo de baixa atividade era associado a um

maior IMC em uma amostra de homens obesos (FUEMMELER et al., 2008). Outro estudo ao

realizar a análise do polimorfismo MAOAu-VNTR revelaram uma tendência para um desequilíbrio

de transmissão entre o alelo de baixa atividade transcricional (alelo curto) era transmitido

preferencialmente aos filhos que apresentavam obesidade (CAMARENA et al., 2004). Embora os

resultados dos trabalhos acima indiquem uma participação do polimorfismo MAOAu-VNTR e

obesidade, ainda não é possível determinar um alelo de risco.

30

1.5.2 Polimorfismo MAOA T941G

Outro polimorfismo no gene MAOA é encontrado no exon 8 é o T941G, um SNP funcional

onde a ocorrência de guanina (G) na posição 941 cria um sítio de restrição para a enzima Fnu4H1

dentro da região codificante do gene. Embora esta substituição T/G ocorra na terceira base do

códon, e desta forma não afete a estrutura da proteína, ela foi associada com diferentes níveis de

atividade enzimática. Hotamisligil e Breakefield relataram uma associação do alelo 941T com

baixa atividade da enzima MAOA em 40 linhagens de células de atividade conhecida da MAOA

(HOTAMISLIGIL et al., 1991). Já em uma amostra de irlandeses o alelo 941G, de alta atividade, foi

associado com TDAH (DOMSCHKE et al., 2005). Xu et al., também encontraram associação entre

o alelo 941G e risco de desenvolver TDAH (XU et al., 2007). O primeiro estudo realizado

observando a associação entre o polimorfismos T941G e Transtorno de ansiedade generalizada

(TAG), que também tem como fator etiológico aumento nos níveis de serotonina e dopamina no

cérebro, foi publicado em 2003 e encontrou associação entre o alelo 941T e TAG (TÁDIC et al.,

2003). Devido a estas inconsistências da literatura é importante que outros estudos investiguem o

papel do polimorfismo MAOA T941G no gene MAOA e seu papel sobre a ansiedade e

comorbidades associadas como o excesso de ingestão alimentar. Estudos que investiguem a

associação diretamente do polimorfismo MAOA T941G e comportamento alimentar ou obesidade

até o momento não foram realizados.

1.6 Catecol--metiltransferase – Gene COMT

A COMT exerce um papel proeminente na inativação e degradação de catecolaminas e

estrógeno (ANNERBRINK et al., 2008). Esta enzima é expressa de duas formas: uma forma

solúvel (s-COMT) e uma forma ligada a membrana com 50 resíduos adicionais no resíduo N-

31

terminal (mb-COMT) (TENHUNEN et al., 1994). A COMT catalisa a transferência de um grupo

metil da S-adenosilmetionina (SAM) para uma variedade de catecolaminas, incluindo o

neurotransmissor dopamina (MANNISTO & KAAKKOLA, 1999). Ela é uma enzima extracelular

que O-metila a dopamina, sendo a única enzima que é capaz de metabolizar a dopamina neste

espaço. Esta reação pode ocorrer antes ou depois da desaminação pela MAO, localizada na

mitocôndria intraneuronal (SHIELD et al., 2004). Há evidências de que mudanças na atividade da

COMT trazem efeitos centrais e periféricos por alterar as quantidades de dopamina e

noradrenalina na fenda sináptica (KRING et al., 2009). Sendo assim, esta enzima está envolvida

em vários mecanismos recompensa motivado como o aumento da ingestão alimentar (WANG et

al., 2001; HALFORD et al., 2004), humor e outros processos mentais (MANNISTO & KAAKKOLA,

1999; MALHOTRA et al., 2007). Considerando que catecolaminas e hormônios esteróides

exercem influência sobre consumo alimentar (HALFORD et al., 2004) e metabolismo (LOUET et

al., 2004), pode-se correlacionar que a atividade da enzima COMT pode influenciar na

determinação do índice de massa corporal (IMC) e/ou na distribuição de gordura.

1.6.1 Polimorfismo COMT Val158Met

Vários polimorfismos no gene da COMT têm sido descritos, mas o COMT Val158Met

(24938A/G, rs4680) é o mais amplamente estudado, mostrando as associações com câncer de

mama (YIM et al., 2001; WEDRÉN et al., 2003), esquizofrenia (STROUS et al., 2003), transtorno

obsessivo compulsivo (KARAYIORGOU et al., 1997), alcoolismo (KAUHANEN et al., 2000),

transtornos alimentares (MIKOLAJCZYK et al., 2006) e obesidade (WANG et al., 2007). Ele está

localizado no quarto éxon do cromossomo 22q11.21 e se caracteriza pela troca de uma valina por

uma metionina na posição na posição 158 na forma mb-COMT (Val158Met) em conseqüência da

32

troca da base nitrogenada guanina (alelo G) pela base adenina (alelo A) (LUNDSTRÖM et al.,

1995). O polimorfismo Val158Met afeta a atividade e a expressão da COMT, afetando

potencialmente os níveis de dopamina. O alelo Met produz uma proteína termolábil, diminuindo

sua atividade e permitindo, assim, aumento na concentração de dopamina extracelular

(MANNISTO & KAAKKOLA, 1999; SHIELD et al., 2004). Indivíduos portadores do genótipo

Met/Met têm redução de 3 a 4 vezes na atividade de degradação enzimática quando comparados

com portadores do genótipo Val/Val; heterozigotos possuem uma atividade intermediária

(LACHMAN et al., 1996). Os estudos de associação deste polimorfismo com comportamento

alimentar e obesidade apresentam resultados controversos, os dois alelos já foram associados

com aumento de risco para estas condições. Em um estudo publicado em 2006 por NEED et cols.,

não foi detectada associação entre o polimorfismo COMTVal158Met e obesidade.

JUSTIFICATIVA

De acordo com a revisão mais compreensiva na área, o Obesity Gene Map

(RANKINEN et al., 2006), a influência de diversas variantes genéticas no desenvolvimento de

obesidade está sendo investigada por muitos grupos, mas poucos estudos analisaram a

influência destas variantes em crianças e, também, seu efeito na variação de peso com a

idade. Os poucos estudos realizados em relação ao componente genético da obesidade na

população brasileira restringem-se a adultos. A identificação dos indivíduos que são

geneticamente mais susceptíveis a responder às mudanças dietéticas particulares pode ser

importante para a intervenção bem sucedida no tratamento da obesidade. A amostra

analisada neste trabalho possui uma característica inédita, pois numerosos estudos já foram

realizados em adultos, mas relativamente poucos em crianças e, mesmo estes, na sua quase

totalidade consistiram em estudos que não avaliaram as diferenças étnicas como o aqui

proposto.

OBJETIVOS

Investigar a associação das variantes Taq1A e -141C Ins/Del do gene DRD2; variante

MAOA-u VNTR e T941G do gene MAOA; e variante Val158Met do gene COMT na regulação do

peso corporal e os aspectos relacionados à obesidade, dados antropométricos e consumo alimentar

de crianças com idade entre três e quatro anos de idade.

Objetivos específicos

Analisar a associação das variantes Taq1A e -141C Ins/Del do gene DRD2; variante MAOA-

u VNTR e T941G do gene MAOA; e variante Val158Met do gene COMT e o escore Z do

índice de massa corporal.

Investigar a associação das variantes Taq1A e -141C Ins/Del do gene DRD2; variante

MAOA-u VNTR e T941G do gene MAOA; e variante Val158Met do gene COMT e o escore Z

do percentil de dobras cutâneas.

Verificar a associação das variantes Taq1A e -141C Ins/Del do gene DRD2; variante MAOA-

u VNTR e T941G do gene MAOA; e variante Val158Met do gene COMT e circunferência da

cintura.

Verificar a associação das variantes Taq1A e -141C Ins/Del do gene DRD2; variante MAOA-

u VNTR e T941G do gene MAOA; e variante Val158Met do gene COMT com ingestão

alimentar.

CAPÍTULO 2

REFERÊNCIAS BIBLIOGRÁFICAS DA INTRODUÇÃO

36

ANGELIS, R. C. Alimentação na infância vs conseqüências ulteriores na saúde. Rev Paul Ped 1995; 13: 126-7.

ANNERBRINK, K., WESTBERG L., NILSSON, S., ROSMOND, R., HOLM, G., ERIKSSON, E. Catechol O-methyltransferase val158-met polymorphism is associated with abdominal obesity and blood pressure in men. Metabolism 2008; 57 (5): 708-1

ARINAMI, T., GAO, M., HAMAGUCHI, H., TORU, M. A functional polymorphism in the promoter region of the dopamine D2 receptor gene is associated with schizophrenia. Hum Mol Genet 1997; 6: 577–582

BATISTA FILHO, M., RISSIN, A. A transição nutricional no Brasil: tendências regionais e temporais. Cad Saúde Publ 2003; 19 (1): 181S-91S.

BALCIUNIENE, J., EMILSSON, L., ORELAND, L., PETTERSSON, U., JAZIN, E. Investigation of the functional effect of monoamine oxidase polymorphisms in human brain. Hum Genet. 2002 Jan; 110 (1): 1-7.

BEAUCHAMP, G. K., MENNELLA, J. A. A alimentação nas primeiras etapas da vida e o desenvolvimento das preferências pelos sabores. Resumo do 36º Seminário Nestlé Nutrition 1994; p. 27-9.

BELLO, N. T., LUCAS, L. R., HAJNAL, A. Repeated sucrose access influences dopamine D2 receptor density in the striatum. Neuroreport. 2002; 13: 1575-1578.

BIRCH, L. L. Psychological influences on the childhood diet. J Nutr 1998; 128: 407s-10s. BIRCH, L. L., FISHER, J. A. The role of experience in the development of children’s eating behavior. In:

Capaldi ED, editor. Why we eat what we eat. The psychology of eating. 2ª ed. Washington: APA; 1997. p. 113-41.

BLUM, K., CHEN, T. J., MESHKIN, B., DOWNS, B. W., GORDON, C. A., BLUM, S., MANGUCCI, J. F., BRAVERMAN, E. R., ARCURI, V., DEUTSCH, R., PONS, M. M. Genotrimtrade mark, a DNA-customized nutrigenomic product, targets genetic factors of obesity: Hypothesizing a dopamine-glucose correlation demonstrating reward deficiency syndrome (RDS). Med Hypotheses 2007; 68 (4): 844-852.

CABRAL, A., NICK, E. Dicionário Técnico de Psicologia. São Paulo: Cultrix; 1974. CAMARENA, B., SANTIAGO, H., AGUILAR, A., RUVINSKIS, E., GONZALEZ-BARRANCO, J. &

NICOLINI, H. Family-based association study between the monoamine oxidase A gene and obesity: implications for psychopharmacogenetic studies. Neuropsychobiology, 2004. 49, 126–129.

CAPALDI, E. Conditioned food preferences. In: Capaldi ED, editor. Why we eat what we eat. The psychology of eating. 2ª ed. Washington: APA; 1997; 53-80.

CHEN, K. Organization of MAO A and MAO B promoters and regulation of gene expression. Neurotoxicology 2004; 25: 31-36.

CHIBA, K., TREVOR, A., CASTAGNOLI, N., JR. Metabolism of the neurotoxic tertiary amine, MPTP, by brain monoamine oxidase.Biochem Biophys Res Commun 1984; 120, 574-578.

COLANTUONI, C., SCHWENKER, J., MCCARTHY, J., RADA, P., LADENHEIM, B., CADET, J. L., SCHWARTZ, G. J., MORAN, T. H., HOEBEL, B. G. Excessive sugar intake alters binding to dopamine and mu-opioid receptors in the brain. Neuroreport. 2001; 12: 3549-3552.

DAVIS, C. A., LEVITAN, R. D., REID, C., CARTER, J. C., KAPLAN, A. S., PATTE, K. A., KING, N., CURTIS, C., KENNEDY, J. L. Dopamine for "Wanting" and Opioids for "Liking": A Comparison of Obese Adults With and Without Binge Eating. Obesity, 2009. 17: 1220-1225;

37

DAVIS, C., PATTE, K., LEVITAN, R. D., REID, C., TWEED, S., CURTIS, C. From motivation to behaviour: a model of reward sensitivity, overeating, and food preferences in the risk profile for obesity. Appetite 2007; 48: 12–9.

DAVIS, C., STRACHAN, S., BERKSON, M. Sensitivity to reward: implications for overeating and overweight. Appetite 2004; 42: 131-138.

DAVIS, C., WOODSIDE, D. B. Sensitivity to the rewarding effects of food and exercise in the eating disorders. Compr Psychiatry 2002;43:189–94.

DECKERT, J., CATALANO, M., SYAGAILO, Y. V., BOSI, M., OKLADNOVA, O., DI BELLA, D., NO¨THEN, M. M., MAFFEI, P., FRANKE, P., FRITZE, J., MAIER, W., PROPPING, P., BECKMANN, H., BELLODI, L., LESCH, K. P. Excess of high activity monoamine oxidase A gene promoter alleles in female patients with panic disorder. Hum. Mol. Genet. 1999; 8: 621–624.

DENNEY, R. M., KOCH, H., CRAIG, I. W. Association between monoamine oxidase A activity in human male skin fibroblasts and genotype of the MAOA promoter-associated variable number tandem repeat. Hum Genet. 1999; 105: 542– 551.

DOMSCHKE, K., SHEEHAN, K., LOWE, N., KIRLEY, A., MULLINS, C., O'SULLIVAN, R., FREITAG, C., BECKER, T., CONROY, J., FITZGERALD, M., GILL, M., HAWI, Z. Association analysis of the monoamine oxidase A and B genes with attention deficit hyperactivity disorder (ADHD) in an Irish sample: preferential transmission of the MAO-A 941G allele to affected children. Am J Med Genet B Neuropsychiatr Genet. 2005; 134B: 110-114.

EPSTEIN, L. H., LEDDY, J. J. Food reinforcement. Appetite. 2006; 46: 22-25. EPSTEIN, L. H., TEMPLE, J. L., NEADERHISER, B. J., SALIS, R. J., et al. Food reinforcement, the

dopamine D2 receptor genotype, and energy intake in obese and nonobese humans. Behav. Neurosci. 2007, 121, 877-889.

EKBLOM, J., GARPENSTRAND, H., DAMBERG, M., CHEN, K., SHIH, J. C., ORELAND, L. Transcription factor binding to the core promoter of the human monoamine oxidase B gene in the cerebral cortex and in blood cells. Neurosci Lett 1998. 258: 101–104.

EKLUND, J., ALM, P. O., af KLINTEBERG, B. Monoamine oxidase activity and tri-iodothyronine level in violent offenders with early behavioural problems. Neuropsychobiology. 2005; 52 (3): 122-129.

FANG, Y. J., THOMAS, G. N., XU, Z. L., FANG, J. Q., CRITCHLEY, J. A., TOMLINSON, B. An affected pedigree member analysis of linkage between the dopamine D2 receptor gene TaqI polymorphism and obesity and hypertension. Int J Cardiol 2005; 102 (1):111-6.

FERREIRA, A. B. H. Minidicionário da Língua Portuguesa. 6a ed. Positivo; 2004. FOWLER, J. B., MACGREGOR, R.R., WOLF, A. P., ARNETT, C. D., DEWEY, S. L., SCHLYER, D.,

CHRISTMAN, D. Mapping human brain monoamine oxidase A and B with 11C-labelled suicide inactivators and PET. Science 1987; 235: 481-485

FRANKEN, I. H. A., MURIS, P. Individual differences in reward sensitivity are related to food craving and relative body weight in healthy women. Appetite 2005; 45: 198–201.

FURLONG, R. A., HO, l., RUBINSZTEIN, J. S., WALSH, C., PAYKEL, E. S., RUBINSZTEIN, D. Ananalyses of the Monoamine Oxidase A (MAOA) Gene in Bipolar Affective Disorder by Association Studies, Meta-Analyses, and Sequencing of the Promotor. Am J Med Genet. 1999; 88: 398-406.

FUEMMELER, B. F., AGURS-COLLINS, T. D., MCCLERNON, F. J., KOLLINS, S. H., KAIL, M. E., BERGEN, A. W., ASHLEY-KOCH, A. E. Genes Implicated in Serotonergic and Dopaminergic Functioning Predict BMI Categories. Obesity. 2008; 16, 348–355.

38

GARPENSTRAND, H., EKBLOM, J., FORSLUND, K., RYLANDER, G., ORELAND, L. Platelet monoamine oxidase activity is related toMAOBintron 13 genotype. J Neural Transm 2000; 107: 523–30.

GARRICK, N. A., MURPHY, D. L. Monoamine oxidase type A: differences in selectivity towards norepinephrine compared to serotonin. Biochem Pharmacol 1982; 31: 4061-4066.

GOUDIE, A. J., HALFORD, J. C., DOVEY, T. M., COOPER, G. D., NEILL, J. C. H(1)-histamine receptor affinity predicts short-term weight gain for typical and atypical antipsychotic drugs. Neuropsychopharmacology. 2003; 28: 2209-2211.

GRIMSBY, J., CHEN, K., WANG, L. J., LAN, N. C., SHIH, J. C. Human monoamine oxidase A and B genes exhibit identical exon-intron organization. Proc Natl Acad Sci U S A. 1991; 88 (9): 3637-41.

HALFORD, J. C., COOPER, G. D., DOVEY, T. M. The pharmacology of human appetite expression, Curr Drug Targets. 2004; 5, pp. 221–240.

HALTIA, L. T., RINNE, J. O., MERISAARI, H., MAGUIRE, R. P., SAVONTAUS, E., HELIN, S., NAGREN, K., KAASINEN, V. Effects of intravenous glucose on dopaminergic function in the human brain in vivo. Synapse. 2007; 61: 748-756.

HAMARMAN, S., FOSSELLA, J., ULGER, C., BRIMACOMBE, M., DERMODY, J. Dopamine receptor 4 (DRD4) 7-repeat allele predicts methylphenidate dose response in children with attention deficit hyperactivity disorder: A pharmacogenetic study. Journal of Child and Adolescent Psychopharmacology 2004; 14: 564-574.

HERNÁN M. A., CHECKOWAY, H., O'BRIEN, R., COSTA-MALLEN, P., De VIVO, I., COLDITZ, G. A., HUNTER, D. J., KELSEY, K. T., ASCHERIO, A. MAOB intron 13 and COMT codon 158 polymorphisms, cigarette smoking, and the risk of PD.Neurology. 2002; 58 (9): 1381-7.

HOTAMISLIGIL, G. S., BREAKEFIELD, X. O. Human monoamine oxidase A gene determines levels of enzyme activity. Am J Hum Genet. 1991; 49 (2): 383–392.

HUANG, S. Y., LIN, W. W., WAN, F. J., CHANG, A. J., KO, H. C., WANG, T. J., WU, P. L., LU, R. B. Monoamine oxidase-A polymorphisms might modify the association between the dopamine D2 receptor gene and alcohol dependence. J Psychiatry Neurosci. 2007; 32 (3):185-92.

HUMPHRIES, S. E & ORDOVAS, J. M. Genetics and atherosclerosis: broadening the horizon. Atherosclerosis 2001; 154: 517-519.

INOUE, K., KIRIIKE, N., KURIOKA, M., FUJISAKI, Y., IWASAKI, S., YAMAGAMI, S. Bromocriptine enhances feeding behavior without changing dopamine metabolism. Pharmacol Biochem Behav. 1997; 58 (1): 183-8.

INTERNATIONAL HUMAN GENOME SEQUENCING CONSORTIUM. Initial sequencing and analysis of the human genome. Nature 2001; 409: 860-921.

JÖNSSON, E. G., NOTHEN, M. M., GRUNHAGE, F., FARDE, L., NAKASHIMA, Y., PROPPING, P., SEDVALL, G. C. Polymorphisms in the dopamine D2 receptor gene and their relationships to striatal dopamine receptor density in healthy volunteers. Mol Psychiatry 1999; 4: 290–296.

JÖNSSON, E. G., NORTON, N., FORSLUND, K., MATTILA-EVENDEN, M., RYLANDER, G., ASBERG, M., OWEN, M. J., SEDVALL, G. C.Association between a promoter variant in the monoamine oxidase A gene and schizophrenia. Schizophr Res. 2003; 61 (1):31-7. Review.

KARAYIORGOU, M., ALTEMUS, M., GALKE, B. L., GOLDMAN, D., MURPHY, D. L., OTT, J., GOGOS, J. A.. Genotype determining low catechol-O-methyltransferase activity as a risk factor for obsessive-compulsive disorder. Proc. Natl. Acad. Sci. U. S. A. 94. 1997; 4572–4575.

KAUER, J. A. Neuroscience: a home for the nicotine habit. Nature. 2005; 436: 31-32. KAUHANEN, J., HALLIKAINEN, T., TUOMAINEN, T. P., KOULU, M., KARVONEN, M. K., SALONEN,

J. T., TIIHONEN, J. Association between the functional polymorphism of catechol-O-

39

methyltransferase gene and alcohol consumption among social drinkers. Alcohol Clin Exp Res. 2000; 24 (2): 135-9.

KIM, H., LEE, H., ROWAN, J., BRAHIM, J., DIONNE, R. A. Genetic polymorphisms in monoamine neurotransmitter systems show only weak association with acute post-surgical pain in humans. Mol Pain. 2006; 2: 24.

KOIVISTO, U. K., SJÖDÉN, P. O. Reasons for rejection of food items in swedish families with children aged 2-17. Appetite 1996; 26: 89-103.

KREBS-SMITH, S. M., COOK, D. A., SUBAR, A. F., CLEVELAND, L., FRIDAY, J., KAHLE, L. L. Fruit and vegetable intakes of children and adolescents in the United States. Arch Pediatr Adolesc Med 1996; 150: 81-6.

KRING, S. I. I., WERGE, T., HOLST, C., TOUBRO, S., ASTRUP, A., HANSEN, T., PEDERSEN, O., SORENSEN, T. I. A. Polymorphisms of Serotonin Receptor 2A and 2C Genes and COMT in Relation to Obesity and Type 2 Diabetes. PLoS ONE. 2009; 4 (8): e6696

KURTH, J. H., KURTH, M. C., PODUSLO, S. E., SCHWANKHAUS, J. D. Association of a monoamine oxidase B allele with Parkinson's Disease. Ann Neurol 1993; 33: 368–72.

LACHMAN, H. M., PAPOLOS, D. F., SAITO, T., YU, Y. M., SZUMLANSKI, C. L., WEINSHILBOUM, R. M. Human catechol-o-methyltransferase pharmacogenetics: description of a functional polymorphism and its potential application to neuropsychiatric disorders. Pharmacogenetics. 1996; 6 (3), 243−250.

LAHIRI, D.K., NURNBERGER, J. I. A rapid non-enzymatic method for the preparation of HMW DNA from blood for RFLP studies. Nucleic Acids Res 1991; 19 (19): 5444.

LAWFORD, B. R., McD YOUNG, R., NOBLE, E. P., KANN, B., ARNOLD, L., ROWELL, J., RITCHIE, T. L. D2 dopamine receptor gene polymorphism: paroxetine and social functioning in posttraumatic stress disorder. Eur Neuropsychopharmacol. 2003; (5): 313-20.

LEWIS, K. K., MAN, L. H.Overweight and obesity in Massachusetts: epidemic, hype or policy opportunity? Issue Brief (Mass Health Policy Forum). 2007; (30): 1-29.

LIONEL, L. L. Association and linkage studies of bipolar affective disorder - a candidate gene strategy [dissertation]. Londres: Instituto de Psiquiatria da Universidade de Londres; 1995.

LOUET, J. F., LEMAY, C., MAUVAIS-JARVIS, F. Antidiabetic actions of estrogen: insight from human and genetic mouse models, Curr Atheroscler. 2004; Rep 6, 180–185.

LOXTON NJ, DAWE S. Alcohol abuse and dysfunctional eating in adolescent girls: the influence of individual differences in sensitivity to reward and punishment. Int J Eat Disord 2001; 29: 455–62.

LOXTON NJ, DAWE S. Reward and punishment sensitivity in dysfunctional eating and hazardous drinking women: associations with family risk. Appetite 2006; 47: 361–71.

LUNDSTRÖM, K., SALMINEN, M., JALANKO, A., SAVOLAINEN, R., ULMANEN, I. Cloning, expression and structure of catechol-O-methyltransferase. Biochim. Biophys. Acta 1251. 1995; 1–10.

MALCZEWSKA-MALEC, M., WYBRANSKA, I., LESZCZYNSKA-GOLABEK, I., PARTYKA, L., HARTWICH, J., JABROCKA, A., KIEC-WILK, B., KWASNIAK, M., MOTYKA, M., DEMBINSKA-KIEC, A. Analysis of candidate genes in Polish families with obesity. Clin Chem Lab Med 2004; 42 (5): 487-93

MALHOTRA, A. K., LENCZ, T., CORRELL, C. U., KANE, J. M Genomics and the future of pharmacotherapy in psychiatry. Int Rev Psychiatry. 2007; 19/5: 523–530.

MANNISTO, P. T., KAAKKOLA, S. Catechol-O-methyltransferase (COMT): biochemistry, molecular biology, pharmacology, and clinical efficacy of the new selective COMT inhibitors. Pharmacol. Revs. 1999; 51; 593–628.

40

MARTI, A. & MARTINEZ, A. Genetics of obesity: gene x nutrient interactions. Int J Vitam Nutr Res. 2006; 76 (4): 184-93.

MATTEVI, V. S., ZEMBRZUSKI, V. M., HUTZ, M. H. Association analysis of genes involved in the leptin signaling pathway with obesity in Brazil. Int J Obes 2002; 26:1179-85.

MATTEVI, V. S., ZEMBRZUSKI, V. M., HUTZ, M. H. A resistin gene polymorphism is associated with body mass index in women. Hum Genet .2004; 115: 208-212

MATTEVI, V. S., ZEMBRZUSKI, V. M., HUTZ, M. H. Impact of variation in ADRB2, ADRB3, and GNB3 genes on body mass index and waist circumference in a Brazilian population. Am J Hum Biol 2006; 18 (2): 182-186.

A) MESSAS, G. P. A participação da genética nas dependências químicas. Rev. Bras.

Psiquiatr. 1999; vol. 21, s.2.

MIKOLAJCZYK, E., ŚMIAROWSKA, M., GRZYWACZ, A., SAMOCHOWIEC, J. Association of Eating Disorders with Catechol- O -Methyltransferase Gene Functional Polymorphism. Neuropsychobiology. 2006; 54: 82–86

MORAN, R. Evaluation and treatment of childhood obesity. Am Fam Physician 1999; 59: 861-8. MORTON, L. M., WANG, S. S., BERGEN, A. W., CHATTERJEE, N., KYALE, P., WELCH, R.,

YEAGER, M., HAYES, R. B., CHANOCK, S. J., CAPORASO, N. E.. DRD2 genetic variation in relation to smoking and obesity in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Pharmacogenet Genomics. 2006; 16 (12): 901-10.

MOZAFFARI, H. & NABAEI, B. Obesity and related risk factors. Indian J Pediatr. 2007; 74 (3): 265-7. MUNAFO, M. R., JOHNSTONE, E. C., WELSH, K. I., WALTON, R. T. Association between the DRD2

gene Taq1A (C32806T) polymorphism and alcohol consumption in social drinkers. Pharmacogenomics J. 2005; 5 (2): 96-101

NEED, A. C., AHMADI, K. R., SPECTOR, T. D., GOLDSTEIN, D. B. Obesity is associated with genetic variants that alter dopamine availability. Ann Hum Genet. 2006; 70 (3): 293-303.

NETTO CA. Psicobiologia do comportamento alimentar. In: Nunes MA, Appolinário JC, Abuchaim AL, Coutinho W. Transtornos alimentares e obesidade. Artes Médicas; 1998: 197-202.

NISOLI E, BRUNANI A, BORGOMAINERIO E, TONELLO C, DIONI L, BRISCINI L, REDAELLI G, MOLINARI E, CAVAGNINI F, CARRUBA MO. D2 dopamine receptor (DRD2) gene Taq1A polymorphism and the eating-related psychological traits in eating disorders (anorexia nervosa and bulimia) and obesity. Eat Weight Disord. 2007; 12 (2): 91-6.

NOBLE, E. P. Addiction and its reward process through polymorphisms of the D2 dopamine receptor gene: a review. Eur Psychiatry. 2000a; 15 (2): 79-89.

NOBLE, E. P. The DRD2 gene in Psychiatric and Neurological Disorders and its Phenotypes. Pharmacogenomics. 2000b; 1: 309-333.

NOBLE, E., BERMAN, S., OZKARAGOZ, T., RITCHIE, T. Prolonged P300 latency in children with D2 dopamine receptor A1 allele. Am J Hum Genet 1994; 54: 658-68.

NOBLE, E., GOTTSCHALK, L., FALLON, J., RITCHIE, T., WU, J. D2 dopamine receptor polymorphism and brain regional glucose metabolism. Am J Med Genet 1997; 74 (2): 162-6.

OHARA, K., NAGAI, M., TANI, K., NAKAMURA, Y., INO, A., OHARA, K. Functional Polymorphism of -141C Ins/Del in the Dopamine D2 Receptor Gene Promoter and Schizophrenia. Psychiatry Res 1998; 81: 117-23.

OLIVEIRA, J. M. Síndrome de Deficiência da Recompensa. In: Cérebro e Mente. Revista Eletronica de divulgação científica em Neurociências, 8, disponível em www.cerebromente.org.br

PARSONS, M. J., MATA, I., BEPERET, M., IRIBARREN-IRISO, F., ARROYO, B., SAINZ, R., ARRANZ, M. J., KERWIN, R. A Dopamine D2 Receptor Gene-related Polymorphism is

41

Associated witch Schizophrenia in a Spanish Population Isolate. Psychiatr Genet 2007; 17: 159-63.

POHIALAINEN, T., RINNE, J., NAGREN, K., LEHIKOINEN, P., ANTTILA, K., SYVALLAHTI, E., HIETALA, J. The Al allele of the human D2 dopamine receptor gene predicts low D2 receptor availability in healthy volunteers. Mol Psychiatry 1998: 3 (3): 256-60.

POPKIN, B., HORTON, S., KIM, S. The nutrition transition and prevention of diet-related chronic diseases in Asia and the Pacific. Asian Development Bank Nutrition and Development series N. 6. Manila, 2001.

RANKINEN, T., ZUBERI, A., CHANGNON, Y. C., WEISNAGEL, S. J., ARGYROPOULOS, G., WALTS, B., et al. The human obesity gene map: the 2005 update. Obesity 2006; 14 (4): 529-644.

REILLY, J. J., METHVEN, E., McDOWELL, Z. C., HACKING, B., ALEXANDER, D., STEWART, L., KELNAR, C. J. Health consequences of obesity. Arch Dis Child. 2003; 88 (9): 748-52. Review.

ROZIN P. Sociocultural influences on human food selection. In: Capaldi ED, ed. Why we eat what we eat. The psychology of eating. 2ª ed. Washington: APA; 1997: 233-63.

SABOL, S., HU, S., HAMER, D. A functional polymorphism in the monamine oxidase A gene promoter. Hum Genet 1998; 103: 273–279.

SCHACHTER, S., GOLDMAN, R., GORDON, A. Effects of fear, food deprivation, and obesity on eating. J Pers Soc Psychol 1968; 10: 91–7.

SCHINDLER, K. M., PATO, M. T., DOURADO, A., MACEDO, A., AZEVEDO, M. H., KENNEDY, J. L., PATO, C. N. Association and Linkage Disequilibrium between a Functional Polymorphism of the Dopamine-2 Receptor Gene and Schizophrenia in a genetically homogeneos Portuguese Population. Mol Psychiatry 2002; 8: 211-21.

SEEMAN, P., GUAN, H. C., van TOL, H. H. M. Dopamine D4 Receptors Elevate in Schizophrenia. Nature 1993; 365: 441-445.

SHEKIM, W. O., BYLUND, D. B., ALEXSON, J., GLASER, R. D., JONES, S. B., HODGES, K., PERDUE, S. Platelet MAO and measures of attention and impulsivity in boys with attention deficit disorder and hyperactivity. Psychiatry Res. 1986; 18: 179-188.

SHIELD, A. J., THOMAE, B. A., ECKLOFF, B. W., WIEBEN, E. D., WEINSHILBOUM, R. M. Human catechol O-methyltransferase genetic variation: gene resequencing and functional characterization of variant allozymes. Mol Psychiatry. 2004; 9, 151–160.

SMALL, D. M., JONES-GOTMAN, M., DAGHER, A. Feeding-induced dopamine release in dorsal striatum correlates with meal pleasantness ratings in healthy human volunteers. Neuroimage. 2003; 19, 1709.

SPLETT PL, STORY M. Child nutrition: objectives for the decade. J Am Diet Assoc 1991; 91: 665-8. STICE, E., SPOOR, S., BOHON, C., SMALL, D. M. Relation between obesity and blunted striatal

response to food is moderated by TaqIA A1 allele. Science. 2008; 322: 449-452. STROUS RD, NOLAN KA, LAPIDUS R, DIAZ L, SAITO T, LACHMAN HM. Aggressive behavior in

schizophrenia is associated with the low enzyme activity COMT polymorphism: a replication study. Am. J. Med. Genet. 120B. 2003; 29–34.

SUZUKI, A., KONDO, T., MIHARA, K., YASUI-FURUKORI, N., ISHIDA, M., FURUKORI, H., KANEKO, S., INOUE, Y., OTANI, K. The -141C Ins/Del Polymorphism in the Dopamine D2 Receptor Gene Promoter Region is Associated with Anxiolytic and Antidepressive Effects during Treatment with Dopamine Antagonists in Schizophrenic Patients. Pharmacogenetics. 2001 Aug; 11 (6): 545-50.

SZCZYPKA, M. S., KWOK, K., BROT, M. D., MARCK, B. T., MATSUMOTO, A. M., DONAHUE, B. A., PALMITER, R. D. Dopamine Production in the Caudate Putamen Restores Feeding in Dopamine-Deficient Mice. Neuron. 2001; 30, 819.

42

TÁDIC, A., RUJESCU, D., SZEGEDI, A., GIEGLING, I., SINGER, I., MÖLLER, H. J., DAHMEN, N. Association of a MAOA Gene Variant With Generalized Anxiety Disorder, but not With Panic Disorder or Major Depression. American Journal of Medical Genetics Part B (Neuropsychiatric Genetics). 2003; 117B: 1–6.

TÁDIC, A., RUJESCU, D., MÜLLER, M. J., KOHNEN, R., STASSEN, H. H., DAHMEN, N., SZEGEDI, A. A monoamine oxidase B gene variant and short-term antidepressant treatment response. Prog Neuropsychopharmacol Biol Psychiatry. 2007; 31 (7): 1370-7.

TENHUNEN, J., SALMINEN, M., LUNDSTROM, K., KIVILUOTO, T., SAVOLAINEN, R., ULMANEN, I. Genomic organization of the human catechol O-methyltransferase gene and its expression from two distinct promoters. Eur. J. Biochem. 1994; 223: 1049–1059.

THORPE, L. W., WESTLUND, K. N., KOCHERSPERGER, L. M., ABELL, C. W., DENNEY, R.M. Immunocytochemical localization of monoamine oxidase A and B in human peripheral tissues and brain. J Histochem Cytochem 1987; 35: 23-32

VITOLO, M. R., BORTOLINI, G.A., DRACHLER, M. L., FELDENS, C. A. Impactos da implementação dos dez passos da alimentação saudável para crianças: ensaio de campo randomizado. Cad Saúde Publ 2005; 21 (5): 1448-1457.

VOLKOW, N. D., FOWLER, J. S., WANG, G. J., GOLDSTEIN, R. Z. Role of dopamine, the frontal cortex and memory circuits in drug addiction: insight from imaging studies. Neurobiol Learn Mem. 2002; 78: 610–624.

WANG, G. J., VOLKOW, N. D., LOGAN, J., PAPPAS, N. R., WONG, C. T., et al. Brain dopamine and obesity. Lancet. 2001; 357/9253: 354–357.

WANG, Y., MONTEIRO, C., POPKIN, B. M. Trends of obesity and underweight in older children and adolescents in the United States, Brazil, China, and Rússia. Am J Clin Nutr 2002a; 75: 975-81.

WANG, G. J., VOLKOW, N. D., FOWLER, J. S. The role of dopamine in motivation for food in humans: implications for obesity. Expert Opin Ther Targets. 2002b; (5): 601-9.

WANG, S. S., MORTON, L. M., BERGEN, A. W., LAN, E. Z., CHATTERJEE, N., KVALE, P., HAYES, R. B., CHANOCK, S. J., CAPORASO, N. E. Genetic variation in catechol-O-methyltransferase (COMT) and obesity in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial. Hum Genet. 2007; 122 (1): 41–49.

WEDRÉN, S., RUDQVIST, T. R., GRANATH, F., WEIDERPASS, E., INGELMAN-SUNDBERG, M., PERSSON, I., MAGNUSSON, C. Catechol-O-methyltransferase gene polymorphism and post-menopausal breast cancer risk.Carcinogenesis. 2003; 24: 681–687.

WEINER, J. D. I. The connections of the dopaminergic system with the striatum in rats and primates: an analysis with respect to the functional and compartmental organization of the striatum. Neuroscience. 2000; 96: 451–474.

WEYLER, W., HSU, Y-P. P., BREAKEFIELD, X. O. Biochemistry and genetics of monoamine oxidase. J Pharmacol Ther 1990; 47: 391-417.

WINBLAD, B., GOTTFRIES, C. G., ORELAND, L., WIBERG, A. Monoamine oxidase in platelets and brains of non-psychiatric and non-neurological geriatric patients. Med Biol 1979; 57:129–132

WU, R. M., CHENG, C. W., CHEN, K. H., LU, S. L., SHAN, D. E., HO, Y. F., CHERN, H. D. The COMT L allele modifies the association between MAOB polymorphism and PD in Taiwanese. Neurology. 2001; 56 (3): 375-82.

YIM, D. S., PARK, S. K., YOO, K. Y., YOON, K. S., CHUNG, H. H., KANG, H. L., AHN, S. H., NOH, D. Y., CHOE, K. J., JANG, I. J., SHIN, S. G., STRICKLAND, P. T., HIRVONEN, A., KANG, D. Relationship between the Val158Met polymorphism of catechol O-methyl transferase and breast cancer. Pharmacogenetics. 2001; 11: 279–286.

43

YOUNG, R. M., LAWFORD, B. R., BARNES, M., BURTON, S. C., RITCHIE, T., WARD, W. K., NOBLE, E. P. Prolactin levels in antipsychotic treatment of patients with schizophrenia carrying the DRD2*A1 allele. Br J Psychiatry. 2004; 185: 147-51.

XU, X., BROOKES, K., CHEN, C.K., HUANG, Y. S., WU, Y. Y., ASHERSON, P. Association study between the monoamine oxidase A gene and attention deficit hyperactivity disorder in Taiwanese samples. BMC Psychiatry. 2007; 7: 10

CAPÍTULO 3

MANUSCRITO 1

(submetido a revista British Journal of Nutrition)

Association of DRD2 TaqIA and -141C InsDel polymorphisms with food intake and anthropometric data in Brazilian children

Association of DRD2 TaqIA and -141C InsDel polymorphisms with food intake and

anthropometric data in Brazilian children

Ananda C. S. Galvão1, Márcia R. Vitolo2, Paula D. B. Campagnolo2, Vanessa S.

Mattevi1,3, Silvana Almeida1,3*.

¹Laboratório de Biologia Molecular, Programa de Pós-Graduação em Ciências da

Saúde, Universidade Federal de Ciências da Saúde de Porto Alegre; ²Departamento de

Saúde Coletiva, Universidade Federal de Ciências da Saúde de Porto Alegre;

³Departamento de Ciências Básicas da Saúde, Universidade Federal de Ciências da

Saúde de Porto Alegre.

Address to which correspondence should be sent:

Dra. Silvana Almeida

Rua: Sarmento Leite, 245 – sala 309

90050-170 Porto Alegre, RS, Brazil

Tel. 55 51 3303-8763

Fax: 55 51 3303-8718

e-mail: silvana.almeida@pq.cnpq.br

Running title: DRD2 gene: nutritional and anthropometric data

Keywords: child obesity; DRD2 polymorphisms; food intake

Effective interventions to reduce obesity and related health risks are increasingly important

because the number of obese adults and children has reached epidemic proportions. There

are data supporting a role for allelic variants of the D2 dopamine receptor (DRD2) gene in

susceptibility to obesity. We assessed the relationships between food intake, anthropometric

data and the DRD2 Taq1A and -141C InsDel genotypes in children. Our sample consisted of

354 children from three to four years of age whose race or ethnicity was self-defined by skin

colour (i.e. white or non-white). Among white children, only 23.6% exhibited the TaqIA*T allele

as compared to 32% in the non-white sample (p=0.028). A similar pattern was observed for

the 141C Del allele (18.4% in white children versus 10.8% in non-white children; p=0.011). In

non-white children, the TaqIA C/C homozygous genotype was associated with higher HLD

intake (median 666.8 kJ) when compared with children carrying the T allele (343.9 kJ,

p=0.009). Further studies evaluating the effects of this polymorphism on the genetic profiles

associated with food consumption patterns and the anthropometry of children from different

populations will provide a better understanding of polymorphisms relationship to nutritional

outcomes.

Paediatric obesity rates have dramatically increased over the past decade (1). Surveys

during the 1990’s in Brazil and the USA showed that an additional 0.5% of the child

population became overweight during each year of that decade (2, 3). This tendency is

especially alarming because an increase in body weight is a major cause of cardiovascular

disease and affects physical and social functioning as well as life quality (4). Obesity

development is influenced by a complex array of genetic, metabolic and neural frameworks

along with behaviour, eating habits and physical activity (5). Obesogenic modern environments

may either overshadow the observable effects of genetic differences or boost them, by

providing a permissive substrate for the expression of susceptibility (6, 7). Despite increased

knowledge of the neural pathways that control appetite and satiety, obesity prevalence

continues to rise. The ingestion of energy-rich diets and palatable foods has been linked to

changes in stress and reward pathways in the brain (8).

Dopaminergic (DA) pathways are hypothesized to regulate the behavioural and

metabolic responses associated with the development of obesity through feeding and satiety

(9). The central DA reward pathway appears to be involved in the reinforcing effect received by

the brain after a pleasurable experience such as the use of certain drugs (10–12). Drugs that

stimulate this pathway have a positive reinforcing action that leads to addiction. Food has also

been proposed to be such a reinforcing agent (10, 12). Feeding is associated with dopamine

release in the dorsal striatum, and the degree of pleasure from eating correlates with the

amount of dopamine release (13, 14). Stimulation of this pathway may reduce the effectiveness

of satiety factors, thus promoting overeating and leading to an increase in body weight (10).

Since this hypothesis was proposed, several efforts have been made to identify the key

molecular components of dopamine neurotransmission that influence obesity. A growing area

of research has begun to explore the potential association between specific candidate genes

that regulate the brain dopamine system and obesity (15). In the context of a molecular genetic

approach to the problem, several candidate genes among potentially many others related to

this hypothesised vulnerability would include 1) any of the five known dopamine receptor

genes, 2) genes coding for important enzymes of dopamine metabolism, and 3) the dopamine

transporter protein (16). Pharmacological data have suggested that the dopamine D2 receptor

(DRD2) may be involved in excessive body fat accumulation. It was observed that dopamine

antagonist administration increases appetite, energy intake and weight gain in rats and in

schizophrenic patients (17, 18), whereas dopamine agonists reduce food intake and produce

weight loss (19). The DRD2 gene harbours at least two polymorphic functional variants. Civelli

et al. (20) cloned the human DRD2 gene in rats and humans (21) and described the DRD2

TaqIA polymorphism (rs1800497), which is a C/T single nucleotide polymorphism (SNP)

approximately 10 kb centromeric to the DRD2 stop codon on 11q23. This polymorphism

correlates with the reduced expression of D2 receptors (22). Another polymorphism described

by Ohara et al. (23) (DRD2 -141C InsDel; rs1799732) is a single base pair cytosine

insertion/deletion at position -141 in the promoter region and is directly correlated with

receptor expression in vitro (24).

A better understanding of the role of inter-individual variation in the DA system with

respect to motivation for energy intake will guide the development of prevention strategies

and better therapeutic and/or behavioural interventions for obesity. The purpose of our study

was to investigate potential associations of the DRD2 TaqIA and -141C InsDel

polymorphisms with food intake and anthropometric measurements in children from three to

four years of age.

Materials and Methods

Subjects

The sample used in this study consisted of 354 children from three to four years of age.

This study is a cross-sectional examination of children who had participated in a randomised

trial that occurred during their first year of life. All eligible mothers were informed by

fieldworkers about both the overall aims of the study (advice on feeding of infants and its

effects on the child's health) as well as all research procedures, including the use of a

questionnaire, anthropometric and blood haemoglobin measurements, dental examinations

and differences between the intervention and control groups. Race or ethnicity was self-

defined by skin colour (i.e., whites and non-whites) as officially used in demographic

censuses in Brazil. More details of the traits studied are described in Vitolo et al. (25). This

study was conducted according to the guidelines laid down in the Declaration of Helsinki. The

study protocol was approved by the Ethics Committee of the Universidade Federal de

Ciências da Saúde de Porto Alegre (n. 286/06), and all participants provided written informed

consent before commencing the study.

Nutritional status assessed at 3-4 years old

The child’s nutritional status was assessed by means of anthropometric measures in all

visits. Weight was assessed using a portable digital scale and height was assessed using a

portable stadiometer. Their nutritional status was estimated using the body mass index (BMI)

for age charts from the International Child Growth Standards released by the World Health

Organization (26). The waist circumference was measured at the minimum circumference

between the iliac crest and the rib cage using an inflexible measuring tape. Triceps skinfold

and subscapular skinfold were measured using a Lange skinfold caliper to the nearest 1.0

mm. Each skinfold was measured two times on the right side of the body and was analysed

as z-score according to Multicentre Growth Study standard charts (26).

Dietary data assessed at 3-4 years old

Two 24-hour dietary recalls were collected for each child on two randomly selected

days. A food portion measurement aid and the common household measures (eg, teaspoons,

tablespoons, cups) were used to quantify portion sizes.

Dietary information was entered into the Nutrition Support Program software from the

Escola Paulista de Medicina, Federal University of São Paulo, based on United States

Department of Agriculture chemical composition tables. The energy intake was calculated

using the average of two diet recalls. We considered high sugar density food (HSD) if the

percentage of simple carbohydrates in 100 grams was higher than 50% and high lipid density

food (HLD) if greater than 30% fat per 100 grams. The calories provided by those foods

groups were studied separately, for statistical analysis.

DNA analyses

Genomic DNA was extracted from peripheral blood leukocytes by the Lahiri and

Nurnberger procedure (28). DRD2 TaqIA (rs1800497) and -141C InsDel (rs1799732)

polymorphisms were detected by PCR-RFLP analysis using primer sequences and conditions

described by Hamarman at al. and Ohara et al. (29, 23), respectively. Primers sequences (IDT

Coralville, IA, USA) were as follows: TaqIA, forward primer 5’-

CACCTTCCTGAGTGTCATCAA -3’ and reverse primer 5’-AGACAACTTGGCCAGCCGTG-3’;

-141C InsDel, forward primer 5’-ACTGGCGAGCAGACGGTGAGG and reverse primer 5’-

TGCGCGCGTGAGGCTGCCGGT. PCR products were digested separately with either TaqI

(TaqIA polymorphism) or MvaI (-141C InsDel polymorphism) enzyme (Fermentas, Glen

Burnie, MD, USA), according to the manufacturer’s instructions. Genotypes were determined

after electrophoresis in 2% or 3% agarose gels that had been stained with ethidium bromide.

For the DRD2 TaqIA polymorphism, the C allele contains a TaqI restriction site and is also

designated as the A2 allele, while the T allele is designated as the A1 allele. For the -141C

InsDel polymorphism, the -141C Ins allele contains a restriction site for MvaI while the -141C

Del allele does not.

Statistical analyses

Allele frequencies were estimated by gene counting. A χ² test for goodness-of-fit was

used to determine whether the observed genotype frequency distributions agreed with those

expected under Hardy-Weinberg equilibrium. Haplotype frequencies and linkage

disequilibrium were estimated using the Multiple Locus Haplotype Analysis program, Version

2.0 (30, 31) and Arlequin software, Version 3.1 (32).

Pearson’s chi-squared or Fisher’s Exact Test was used to compare genotype or allele

frequencies, respectively, for polymorphisms between white and non-white children. The

association analyses were performed separately in white and non-white samples. Mean or

median kilocalories of food cluster intake (HSD and HLD), total energy/day and

anthropometric parameters (waist circumference, triceps skin fold Z-score and subscapular

skin fold Z-score) were compared among the different genotypes by the Student’s t test for

independent samples or the Mann-Whitney U test, depending on the variable distributions. All

tests and transformations were performed using the Statistical Package for Social Sciences,

Version 16.0 (SPSS®, Chicago, IL, USA).

Results

Mean ages for the children in this study were 4.1 0.9 years old (mean SD), of which

41.7% were white and 57.2% were boys. Genotype frequency distributions observed for both

polymorphisms studied did not reveal statistically significant differences when compared to

those expected under Hardy-Weinberg equilibrium, for both the DRD2 TaqIA polymorphism in

white (χ²=0.973, 2DF, p=0.614) and non-white children (χ²=0.000, 2DF, p=1.000) and for the

DRD2 -141C InsDel polymorphism in non-white (χ²=0.251, 2DF, p=0.882) and white children

(χ²=0.560, 2DF, p=0.756). Allele and genotype frequencies for the two studied polymorphisms

are presented in Table 1. The frequency of the DRD2 TaqIA*T allele was significantly higher

in non-white (0.320) than in white children (0.236; p=0.028), and genotype frequencies were

also different for non-white versus white children (p=0.048). The frequency of the DRD2 -

141C Del allele was significantly higher in non-white (0.184) than in white children (0.108;

p=0.011), and the DRD2 -141C InsDel genotype frequencies were different between non-

white and white children (p=0.034). The two gene variants were not in linkage disequilibrium

(white children: D’=0.689, χ²=0.040, DF=1, p= 0.840; non-white children: D’=0.031, χ2=0.141,

DF=1, p=0.707). The DRD2 -141C InsDel polymorphism was not associated with food intake

and anthropometric data when analyzed in white and non-white children (Tables 2 and 3). In

non-white children, the TaqIA C/C homozygous genotype was associated with higher HLD

intake (median 666.8 kJ) when compared with children carrying the T allele (343.9 kJ,

p=0.009; Table 2).

Discussion

The allele and genotype frequencies of the polymorphisms found in white and non-

white samples were similar to those described in other European-American and African-

American populations, respectively (33, 34). In the present study, as also reported by O’Hara et

al. (35), the -141C InsDel polymorphism in the promoter region of DRD2 and the TaqIA

polymorphism were not in linkage disequilibrium (LD). This finding can be explained because

these two polymorphisms are distant from each other in the DRD2 chromosomal region.

However, Gelernter et al. (34) found significant LD between the -141C InsDel and TaqIA

polymorphisms in African-American subjects, a finding that we did not replicate when

analysing only non-white samples.

There is increasing evidence for a role of the dopaminergic pathway in the

development of obesity. More specifically, DA hypoactivity might lead to overcompensatory

food intake. Eating and DA signalling are closely related. Food rewards and their associated

stimuli both elevate dopamine levels in crucial components of brain reward circuits (36). In fact,

food might be the most important natural stimulus for the reward system in the brain

(37). Small et al. (13) suggest that the amount of released dopamine correlates with the degree

of experienced pleasure. Some studies have shown that the presence of the T (A1) allele

(polymorphism TaqIA) is associated with a 40% reduction in D2 receptor expression without

changing the receptor affinity, and this phenomenon results in DA hypoactivity (38, 39).

The DRD2 TaqIA polymorphism is associated with increased BMI (40, 41), obesity (42-45),

Reward Deficiency Syndrome (45) and the differential therapeutic effects of chromium

picolinate with respect to weight loss and changes in body fat (46). This variant has been

associated with food intake, such that individuals carrying the T (A1) allele have higher food

reinforcement (are willing to work harder for food) and consume more food than their

counterparts without the T (A1) allele (47, 48). These findings suggest that DRD2 variations

affect nutritional status through modulating food craving behaviour. It is noteworthy that none

of the studies cited above included children in their samples. The few studies that investigated

the influences of the TaqIA polymorphism in children have focused on Attention Deficit

Hyperactivity Disorder (29, 48), and a recent study evaluated food consumption in response to

methylphenidate, focusing on polymorphisms related to the availability of dopamine. That

study found an association between C/C homozygous children and reduced dietary intake in

response to methylphenidate (49).

In the present study, the TaqIA C/C (A2/A2) homozygous genotype was associated

with higher intake of HLD when compared with the TaqIA*T (A1) allele carriers in non-white

children. However, the T (A1) allele of the DRD2 TaqIA polymorphism is generally associated

with decreased DRD2 function or expression (50). Thus, our results are apparently

contradictory to what should be expected regarding the functional effect of this polymorphism.

Nevertheless, Miyake et al. (51) investigated the association of idiopathic short stature with the

DRD2 TaqIA polymorphism in a Japanese population, and their results suggest that the T

(A1) allele may differ in its linkage disequilibrium among different populations. One other

studies conducted by Davis et al. (2008) also found an inverse relationship to what was

expected. In this study they observed in the Individuals with binge eating disorder (BED) and

obese participants, significantly higher reward sensitivity was found in the T (A1) + groups.

One reason could be that the BED and obese (but not the normal-weight) participants

possess another genetic variant that interacts with the T (A1) allele to produce higher DA

activity. The findings of a recent study are cognate to this possibility (52). Reuter et al. (2006)

have provided evidence for a gene interaction model between the catabolic enzyme activity of

catechol-O-methyl transferase (COMT) and DRD2 receptor density, whereby disequilibrium is

associated with higher DA levels and higher Behavioural Activation (BAS) scores. In other

words, high enzyme activity (associated with the Val allele of COMT) and low D2 receptor

density (associated with the T (A1) allele) contribute to relatively high DA levels and

correspondingly elevated reward sensitivity scores on the BAS scale (53). Since the T (A1)

allele is not itself thought to be a functional polymorphism in the DRD2 gene, variations in

genetic background (i.e., different patterns of linkage with actual functional genetic

polymorphisms) could explain varying results across populations. There are several studies

that have replicated a previously reported disease-marker association, with the effect of the

risk allele being opposite from that in the previous report. These associations with

contradictory results may indeed be confirmations but multilocus effects and variation in

interlocus correlations might contribute to a flip-flop phenomenon (54).

Based on previous research suggesting that BMI associations with dopamine receptor

polymorphisms are due to increased food craving (24), we expected that BMI would be related

to the dopamine receptor genotype. However, food craving in Western environments of food

surpluses might have very different contexts than in populations with different food availability.

Adeyemo et al. (55) performed a genome-wide scan in a black population for markers

associated with obesity and found an association with chromosome 11, in the exact area

where the DRD2 gene is located. There have been many positive reports suggesting an

association between DRD2 alleles and obesity in people of European descent but not in

African-American subjects (15, 18, 40- 44, 46, 48, 56).

Luciferase reporter assays demonstrated that transient enzymatic activity and therefore

transcription is significantly silenced in clones containing the deletion variant (-141C Del)

compared to the insertion variant (-141C Ins) (57). Arinami et al. (24) reported that the -141C

Del allele decreases the promoter activity of the DRD2 gene in cell cultures. Other studies

produced conflicting results (58, 59). We found no association between alleles of the

polymorphism DRD2 -141C InsDel and any anthropometric variables or food consumption. To

our knowledge, no other studies to date have been conducted to analyse the association of

the polymorphism DRD2 -141C InsDel with food intake or with anthropometric data.

An inherent limitation to our study is the moderate sample size, which may not have

enough power to detect an association of polymorphisms with small effects on food intake

and anthropometric measurements, such as -141C InsDel. However, we believe the size of

our sample was sufficient to detect relatively large genetic effects, reinforcing the importance

of our findings relating TaqIA to a higher intake of HLD. The present results must be regarded

with caution and should be confirmed in a larger study. At this time, it is important to highlight

another detail that is relevant to our results: the observation that a non-association with

obesity-related anthropometric phenotypes may be due to the fact that children are small and

their time of exposure to an obesogenic environment has not been sufficient to counteract

excessive weight gain. We believe that a follow-up to the present sample may provide

interesting findings for the future. Further studies evaluating the effects of these

polymorphisms on the genetic profiles of food consumption patterns and the anthropometry of

children of different populations would be very relevant for a better understanding of

polymorphism influence on nutritional outcomes.

Acknowledgments

This work was supported by Conselho Nacional de Desenvolvimento Científico e

Tecnológico (CNPq, Brazil; grant number 471186/2009-0), Fundação de Amparo a Pesquisa

do Estado do Rio Grande do Sul (FAPERGS, Brazil; grant number 070026-9), Programa de

Bolsas CAPES and PIBIC/CNPq, and PROAP-CAPES.

A. C. S. G. performed DNA and statistical analyses and drafted the manuscript. M.R.V.

supervised the sample collection and participated in writing the manuscript. P.D.B.C. carried

sample data collection. V.S.M. participated in statistical analysing and writing the manuscript.

S.A. supervised the study and participated in statistical analysing and writing the manuscript.

All authors read and approved the final manuscript.

The authors declare no conflicts of interest.

References

1. Wang Y, Monteiro C, Popkin BM (2002) Trends of obesity and underweight in older

children and adolescents in the United States, Brazil, China, and Russian. Am J Clin

Nutr 75, 975-981.

2. Lobstein T, Baur L, Uauy R (2004) Obesity in children and young people: a crisis in public

health. Obes Rev 5, 4-85.

3. Adams KF, Schatzkin A, Harris TB, et al. (2006) Overweight, obesity, and mortality in a

large prospective cohort of persons 50 to 71 years old. N Engl J Med 355, 763-778.

4. Kumanyika SK, Obarzanek E, Stettler N, et al. (2008) Population-based prevention of

obesity: the need for comprehensive promotion of healthful eating, physical activity,

and energy balance: a scientific statement from American Heart Association Council on

Epidemiology and Prevention, Interdisciplinary Committee for Prevention (formerly the

expert panel on population and prevention science). Circulation 118, 428-464.

5. Acosta MC, Manubay J, Levin FR. (2008) Pediatric obesity: parallels with addiction and

treatment recommendations. Harv Rev Psychiatry 16, 80-96.

6. James PT, Leach R, Kalamara E, et al. (2001) The worldwide obesity epidemic. Obes Res

9, 228S-233S.

7. Hedley AA, Ogden CL, Johnson CL, et al. (2004) Prevalence of overweight and obesity

among US children, adolescents, and adults, 1999–2002. JAMA 291, 2847–2850.

8. Kelley AE, Berridge KC. (2002) The neuroscience of natural rewards: Relevance to

addictive drugs. J Neurosci 22, 3306 –3311.

9. Barsh GS, Schwartz MW. (2002) Genetic approaches to studying energy balance:

perception and integration. Nat Rev Genet 3, 589–600.

10. Hoebel BG. (1985) Brain transmitters in food and drug reward. Am J Clin Nutr 42, 1133–

1150.

11. Koob GF. Drugs of abuse: anatomy, pharmacology and function of reward pathways.

(1992) Trends Pharmacol Sci 13, 177–184.

12. Wise RA, Rompre PP. (1989) Brain dopamine and reward. Annu Rev Psychol 40, 191–

225.

13. Small DM, Jones-Gotman M, Dagher A. (2003) Feeding-induced dopamine release in

dorsal striatum correlates with meal pleasantness ratings in healthy human volunteers.

Neuroimage 19, 1709-1715.

14. Szczypka MS, Kwok K, Brot MD, et al. (2001) Dopamine production in the caudate

putamen restores feeding in dopamine-deficient mice. Neuron 30, 819-828.

15. Fuemmeler BF, Agurs-Collins TD, McClernon FJ, et al. (2008) Genes implicated in

serotonergic and dopaminergic functioning predict BMI categories. Obesity (Silver

Spring) 16, 348-355.

16. Gelernter J, Crowe RR. (1997) Candidate genes and psychiatric genetics: Tomorrow

never knows. Psychiatr Ann 27, 262–267.

17. Parada MA, Hernandez L, Puig D, et al. (1990) Dopamine in the lateral hypothalamus

may be involved in the inhibition of locomotion related to food and water seeking. Brain

Res Bull 25, 961–968.

18. Doss FW. (1979) The effects of antipsychotic drugs on body weight: a retrospective

review. J Clin Psychiatry 40, 528 –530.

19. Robbins TW, Everitt BJ (1982). Functional studies of the central catecholamines. Int Rev

Neurobiol 23, 303–365.

20. Civelli O, Bunzow JR, Grandy DK. (1993) Molecular diversity of the dopamine receptors.

Ann Rev Pharmacol Toxicol 33, 281–307.

21. Bunzow JR, Van Tol HH, Grandy DK, et al. (1988) Cloning and expression of a rat D2

dopamine receptor cDNA. Nature 336, 783-7.

22. Grandy DK, Litt M, Allen L, et al. (1989) The human dopamine D2 receptor gene is

located on chromosome 11 at q22-q23 and identifies a TaqI RFLP. Am J Hum Genet

45, 778-785.

23. Ohara K, Nagai M, Tani K, et al. (1998) Functional polymorphism of -141C InsDel in the

dopamine D2 receptor gene promoter and schizophrenia. Psychiatry Res 81, 117-123.

24. Arinami T, Gao M, Hamaguchi H, et al. (1997) A functional polymorphism in the promoter

region of the dopamine D2 receptor gene is associated with schizophrenia. Hum Mol

Genet 6, 577–582.

25. Vitolo MR, Bortolini GA, Dal Bó Campagnolo P, et al. (2008) Effectiveness of a nutrition

program in reducing symptoms of respiratory morbidity in children: A randomized field

trial. Prev Med 47, 384-388.

26. World Health Organization. The WHO Child Growth Standards (2006). Available at

http://www.who.int/childgrowth/standards/en/.

27. Ministério da Saúde. (2002) Guia alimentar para crianças menores de 2 anos. Brasília:

Ministério da Saúde.

28. Lahiri DK, Nurnberger JIJr. (1991) A rapid non-enzymatic method for the preparation of

HMW DNA from blood for RFLP studies. Nucleic Acids Res 19, 5444.

29. Hamarman S, Fossella J, Ulger C, et al. (2004) Dopamine receptor 4 (DRD4) 7-repeat

allele predicts methylphenidate dose response in children with attention deficit

hyperactivity disorder: A pharmacogenetic study. J Child Adolesc Psychopharmacol

14, 564-574.

30. Long J, Williams R, Urbanek M. (1995) An E-M algorithm and testing strategy for multiple-

locus haplotypes. Am J Hum Genet 56, 799-810.

31. Peterson R, Goldman D, Long J. (1999) Nucleotide sequence diversity in non-coding

regions of ALDH2 as revealed by restriction enzyme and SSCP analysis. Hum Genet

104, 177-187.

32. Excoffier L, Laval G, Schneider S. (2005) Arlequin (version 3.0): An integrated software

package for population genetics data analysis. Evol Bioinform Online 1, 47-50.

33. Gelernter J, Kranzler H, Satel SL. (1999) No Association between D2 Dopamine Receptor

(DRD2) Alleles or Haplotypes and Cocaine Dependence or Severity of Cocaine

Dependence in European- and African-Americans. Biol Psychiatry 45, 340–345;

34. Gelernter J, Kranzler H, Cubells JF, et al. (1998) DRD2 Allele Frequencies and Linkage

Disequilibria, Including the -141CIns/Del Promoter Polymorphism, in European-

American, African-American, and Japanese Subjects. Genomics 51, 21–26.

35. O’Hara BF, Smith SS, Bird G, et al. (1993) Dopamine D2 receptor RFLPs haplotypes and

their association with substance use in black and Caucasian research volunteers. Hum

Hered 43, 209–218.

36. Bassareo V, Di Chiara G. (1997) Differential influence of associative and nonassociative

learning mechanisms on the responsiveness of prefrontal and accumbal dopamine

transmission to food stimuli in rats fed ad libitum. J Neurosci 17, 851-861.

37. Epstein LH, Leddy JJ. (2006) Food reinforcement. Appetite 46, 22-25.

38. Noble EP, Blum K, Ritchie T, et al. (1991) Allelic association of the D2 dopamine receptor

gene with receptor-binding characteristics in alcoholism. Arch Gen Psychiatry 48, 648–

54.

39. Thompson J, Thomas N, Singlelot A, et al. (1997) D2 dopamine receptor gene (DRD2)

TaqI A polymorphism: reduced dopamine D2 receptor binding in the human striatum

associated with the A1 allele. Pharmacogenetics 7, 479–484.

40. Spitz MR, Detry MA, Pillow P, et al. (2000) Variant alleles of the D2 dopamine receptor

gene and obesity. Nutr Res 20, 371–380.

41. Comings DE, Gade R, MacMurray JP, et al. (1996) Genetic variants of the human obesity

(OB) gene: Association with body mass index in young women, psychiatric symptoms,

and interaction with the dopamine D-2 receptor (DRD2) gene. Mol Psychiatry 1, 325–

335.

42. Morton LM, Wang SS, Bergen AW, et al. (2006) DRD2 genetic variation in relation to

smoking and obesity in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening

Trial. Pharmacogenet Genomics 16, 901–910.

43. Jenkinson CP, Hanson R, Cray K, et al. (2000) Association of dopamine D2 receptor

polymorphisms Ser311Cys and TaqIA with obesity or type 2 diabetes mellitus in Pima

Indians. Int J Obes 24, 1233–1238.

44. Southon A, Walder K, Sanigorski AM, et al. (2003) The Taq IA and Ser311Cys

polymorphisms in the dopamine D2 receptor gene and obesity. Diabetes Nutr Metab

16, 72–76.

45. Chen TJH. (2007) Reviewing the role of putative candidate genes in "Neurobesigenics," a

clinical subtype of Reward Deficiency Syndrome (RDS). Gene Ther Mol Biol 11A, 61–

74.

46. Chen TJH, Blum K, Kaats G, et al. (2007) Chromium Picolinate (CrP) a putative anti-

obesity nutrient induces changes in body composition as a function of the Taq1

dopamine D2 receptor polymorphisms in a randomized double-blind placebo controlled

study. Gene Ther Mol Biol 11B, 161–170.

47. Epstein LH, Wright SM, Paluch RA, et al. (2004) Relation between food reinforcement and

dopamine genotypes and its effect on food intake in smokers. Am J Clin Nutr 80, 82–

88.

48. Epstein LH, Temple JL, Neaderhiser BJ, et al. (2007) Food reinforcement, the dopamine

D2 receptor genotype, and energy intake in obese and nonobese humans. Behav

Neurosci 121, 877-889.

49. Leddy JJ, Waxmonsky JG, Salis RJ, et al. (2009) Dopamine-related genotypes and the

dose-response effect of methylphenidate on eating in attention-deficit/hyperactivity

disorder youths. J Child Adolesc Psychopharmacol 19, 127-136.

50. Eisenberg DTA, MacKillop J, Modi M, et al. (2007) Examining Impulsivity as an

Endophenotype Using a Behavioral Approach: A DRD2 TaqIA and DRD4 48-bp VNTR

Association Study. Behav Brain Funct 10, 3-2.

51. Miyake H, Nagashima K, Onigata K, et al. (1999) Allelic variations of the D2 dopamine

receptor gene in children with idiopathic short stature. J Hum Genetics 44, 26–29.

52. Davis, CA, Levitan, R.D, Kaplan, AS, et al. (2008) Reward sensitivity and the D2 dopamine

receptor gene: A case-control study of binge eating disorder. Prog

Neuropsychopharmacol Biol Psychiatry. 32, 620-628.

53. Reuter M, Schmitz A, Corr P, Hennig J. (2006) Molecular genetics support Gray's

personality theory: the interaction of COMT and DRD2 polymorphisms predicts the

behavioural approach system. Int J Neuropsychopharmacol. 9, 155–156.

54. Lin PI, Vance JM, Pericak-Vance MA, et al. (2007) No gene is an island: the flip-flop

phenomenon. Am J Hum Genet 80, 531-538.

55. Adeyemo A, Luke A, Cooper R, et al. (2003) A genome-wide scan for body mass index

among Nigerian families. Obes Res 2, 266-273.

56. Wang GJ, Volkow ND, Logan J, et al. (2001) Brain dopamine and obesity. Lancet 357,

354–357.

57. Stöber G, Jatzke S, Heils A, et al. (1998) Insertion/deletion variant (-141C Ins/Del) in the

50 regulatory region of the dopamine D2 receptor gene: lack of association with

schizophrenia and bipolar affective disorder. J Neural Transm 105, 101–109.

58. Jönsson EG, Nothen MM, Grunhage F, et al. (1999) Polymorphisms in the dopamine D2

receptor gene and their relationships to striatal dopamine receptor density of healthy

volunteers. Mol Psychiatry 4, 290–296.

59. Pohjalainen T, Nagren K, Syvalathi EK, et al. (1999) The dopamine receptor 50-flanking

variant, -141C Ins/Del, is not associated with reduced dopamine D2 receptor density in

vivo. Pharmacogenetics 9, 505–509.

Table 1

Distributions of the TaqIA e -141 InsDel polymorphisms alleles and genotype frequencies in white and non-white children

from three to four years of age.

TaqIA White (n = 127) Non-white (n = 175) P

Alelle/genotype Frequency (n) Frequency (n)

T allele 0.236 (55) 0.320 (94) 0.028a

C/C 0.566 (72) 0.462(81)

T/C 0.393 (50) 0.434 (76)

T/T 0.039 (5) 0.102 (18) 0.037b

-141C InsDel White (n = 127) Non-white (n = 172) P

Alelle/genotype Frequency (n) Frequency (n)

Del allele 0.108 (25) 0.184 (58) 0.011a

Ins/Ins 0.806 (104) 0.672 (119)

Ins/Del 0.170 (22) 0.288 (51)

Del/Del 0.023 (3) 0.039 (7) 0.034b

aFisher’s Exact Test

bPearson Chi-Square

n = individuals number carrier allele/genotype

Table 2

Food intake according TaqIA and -141C InsDel polymorphisms genotypes in white and non-white children from three to four

years of age.

White Children Non-white Children

TaqIA T Carriers N C/C homozygotes N p T Carriers N C/C homozygotes N p

HSD (kcal) 84.60[37.45–126.86] a 55 101.56[53.06–175.25] a 72 0.063b 95.56 [36.90–178.11] a 94 91.83 [44.19–156.12] a 81 0.957b

HLD (kcal) 108.57[18.66–265.95] a 55 179.81[43.54–290.95] a 72 0.139b 82.20 [0.00–195.01] a 94 159.39 [44.26–272.34] a 81 0.009b

Average energy intake

daily (kcal)

1510.40378.15 c 55 1593.60449.22 c 72 0.271b 1451.50347.25 c 94 1549.30422.30 c 81 0.095 d

-141C InsDel Del Carriers N Ins/Ins homozigotes N p Del Carriers N Ins/Ins homozigotes N p

HSD (kcal) 94.12 [48.10–174.97] a 25 95.05[44.55–143.12] a 102 0.714a 90.30 [45.01–164.00] a 55 92.52 [37.37 – 159.30] a 117 0.941 b

HLD (kcal) 118.00 [38.47–268.42] a 25 140.73[34.08–291.68] a 102 0.504a 91.74 [18.66–224.29] a 55 118.00 [17.07–250.66] a 117 0.735 b

Average energy intake

daily (kcal)

1629.50399.20 c 25 1539.90425.422 c 102 0.341b 1548.20401.71 c 55 1469.90373.26 c 117 0.212 d

HSD indicates high sugar density foods; HLD indicates high lipid density foods; a Median [Interquartile Range]; b Mann-

Whitney U Test; c Mean standard deviation, d Test T for independent sample.

n = individuals number carrier genotype

Table 3

Anthropometric data according TaqIA and -141C InsDel polymorphisms genotypes in white and non-white children from

three to four years of age.

White Children Non-white Children

TaqIA T Carriers N C/C homozygotes N p T Carriers N C/C homozygotes N p

Z-score of BMI 0.3340.980a 57 0.1510.8787a 71 0.269b 0.3600.978a 98 0.2051.516a 82 0.412 b

Waist circumference in cm 51.2543.611a 57 50.6282.815a 70 0.275 b 51.0073.226a 98 50.6154.631a 82 0.511 b

Z-score of triceps skinfolds -0.3831.124a 57 -0.3411.045a 70 0.829 b -0.4631.226a 98 -0.4251.356a 82 0.846 b

Z-score of subescapular skinfolds -0.0321.207a 57 -0.3121.230a 70 0.200 b -0.4971.423a 98 -0.4331.640a 82 0.777 b

-141C InsDel Del Carriers N Ins/Ins homozigotes N p Del Carriers N Ins/Ins homozigotes N p

Z-score of BMI 0.3161.114a 25 0.21270.8798a 103 0.619 b 0.1321.450a 58 0.3891.146a 119 0.204 b

Waist circumference in cm 51.8203.599a 25 50.68633.0716a 102 0.113 b 50.6864.624a 58 50.9413.576a 119 0.680 b

Z-score of triceps skinfolds -0.4581.075a 25 -0.33571.0819a 102 0.611 b -0.6281.275a 58 -0.3351.290a 119 0.162 b

Z-score of subescapular skinfolds -0.1181.188a 25 -0.20341.2367a 102 0.758 b -0.5741.640a 58 -0.3761.459a 119 0.411 b

BMI indicates Body Mass Index; a Mean standard deviation; b Test T for independent sample

n = individuals number carrier genotype

CAPÍTULO 3

MANUSCRITO 2

(em preparação para ser submetido a revista Diabetes, Obesity and Metabolism )

Association evaluate of MAOA-u VNTR, MAOA T941G polymorphisms and

COMT Val158Met with food intake and anthropometric data in Brazilian children

Association of MAOA MAOAu-VNTR and T941G and COMT Val158Met

polymorphisms with food intake and anthropometric data in Brazilian children

Ananda C. S. Galvão1, Raquel C. Krüger1, Paula D. B.Campagnolo2, Vanessa S.

Mattevi1,3, Márcia R. Vitolo2, Silvana Almeida1,3*.

¹Laboratório de Biologia Molecular, Programa de Pós-Graduação em Ciências da

Saúde, Universidade Federal de Ciências da Saúde de Porto Alegre; ²Departamento de

Saúde Coletiva, Universidade Federal de Ciências da Saúde de Porto Alegre;

³Departamento de Ciências Básicas da Saúde, Universidade Federal de Ciências da

Saúde de Porto Alegre.

Address to which correspondence should be sent:

Dra. Silvana Almeida

Rua: Sarmento Leite, 245 – sala 309

90050-170 Porto Alegre, RS, Brazil

Tel. 55 51 3303-8763

Fax: 55 51 3303-8718

e-mail: silvana.almeida@pq.cnpq.br

Keywords:

MAOA and COMT polymorphisms; food intake; children obesity;

Abstract

Several studies have implicated dopamine in appetite regulation. Dopamine

availability is controlled by the enzymes COMT and MAOA, and each gene has a

well-characterized functional variant. In this study we have examined three

functional polymorphisms these genes - T941G and 30-bp repeat polymorphism in

the MAOA and the Val158Met in the COMT, to investigate how heritable variation

in dopamine levels influences the anthropometrics data and food intake in a cross-

sectional examination of 354 children. The MAOA T941G polymorphism showed

no association with anthropometrics data or food intake. We found, however, that

both MAOA-u VNTR and COMT Val158Met polymorphisms, the children with the

high-activity genotypes was associated with increased high lipid density (HLD) food

intake (MAOA-u*long - 134.97kcal [26.43–270.16]; COMT*158Val - 133.79kcal

[44.23–265.80]) when compared with children who are low-activity genotypes

(MAOA-u*short carriers - 60.1kcal [0.00–192.31]; COMT*158Met - 83.37Kcal

[0.00–252.95]), p=0.009 and p=0.008 respectively. The MAOA-u*long was still

associated with an increased high sugar density (HLS) food intake when compared

with MAOA-u*short carriers (p=0.034), the medians were 100.45kcal [54.40–

163.32] and 80.01kcal [37.45–127.11]. This study provides the first indication that

dopamine availability in implicating both the MAOA and COMT variants is involved

in human obesity.

1. Introdution

Obesogenic modern environments have caused marked increases in mean

of the weight in populations over the past few decades [1], but there is still

remarkable variability in weight within populations. There is growing evidence from

family, twin, and adoption studies that there is a heritability component to obesity

[2]. In several studies, obese adults were shown to have less effective down-

regulation of appetite after food consumption [3], and lower sensitivity to gastric

motility [4]. Obese adults also exhibited stronger up-regulation of intake in

response to palatability than did normal-weight controls [5]. Similar findings were

reported in children, obese children show poorer caloric compensation after a

preload [6, 7], increase their food intake more than normal-weight controls after

exposure to food cues [6], have higher levels of snack consumption in the absence

of hunger [8], and score higher on psychometrically assessed “external eating” [9].

Other strong body of research pays particular attention to the fact that food, as like

nicotine and other psychoactive drugs, induces pleasurable sensations. In 1985,

Hoebel [10] suggested that the mesocorticolimbic dopaminergic reward pathways

of the brain had a central role in the neuromodulation of appetite. Further evidence

for this theory came from the observation that dopaminergic agonists suppress

appetite whereas antagonists tend to enhance appetite [11, 12]. Since formulation

this hypothesis, several efforts have been made to identify the key molecular

components of dopamine transmission in obesity. A growing area of research has

begun to explore the potential association between specific candidate genes

regulating brain dopamine system with obesity [13]. In the context of a molecular

genetic approach to the problem, candidate genes related to this hypothesized

vulnerability would include any of the five known dopamine receptor genes, genes

coding for important enzymes of the dopamine metabolism, and the dopamine

transporter protein, among potentially many others [14].

Monoamine oxidase (MAO) is a mitochondrial enzyme involved in the

degradation of biological amines including serotonin, dopamine, and

norepinephrine. In humans, there are two isozymes: monoamine oxidase A

(MAOA) and monoamine oxidase B (MAOB) [15]. The MAOA gene is located on

the short arm of chromosome X [16]. The promoter region of this gene has a

variable number tandem repeat (VNTR) polymorphism, MAOAu-VNTR, which has

been shown to influence gene transcription, alleles with 3.5 and 4 repeats were

found to transcribe the protein more efficiently than the 3 repeat allele. The studies

were discordant with regard to a rare 5 repeat allele [17; 18]. Another

polymorphism in MAOA gene is the MAOA T941G polymorphism (rs6323), a

missense mutation caused by G/T transversion located at position 941 in exon 8,

and was reported to be associated with high (G allele) and low (T allele) MAOA

activity in 40 cell lines in which the activity of MAOA was know [16].

Another enzyme that acts in the degradation of dopamine is the catechol-O-

methyltransferase (COMT). This enzyme plays a prominent role in the inactivation

and degradation of catecholamines and estrogen [19]. There is evidence that

changes in activity of COMT bring central and peripheral effects by altering the

amounts of dopamine and norepinephrine in the synaptic cleft [20]. This enzyme

has been involved in several mechanisms of reward-motivated behavior, such as

obesity [21], mood and other mental processes [22]. The chromosome 22q11.21

region coding for the human COMT gene [23]. Several polymorphisms in the

COMT gene have been described, but the Val158Met (24938A/G, rs4680)

polymorphism is the most widely studied [24]. This polymorphism in the fourth exon

of this gene is characterized by a G to A transition, results in a valine to methionine

substitution at codon 158 of the COMT protein, respectively [23].

On the basis of the hypothesis of dopaminergic reward pathways on the

brain has a central role in the neuromodulation of appetite, we propose that the

altered activities or levels of dopamine-regulating enzymes might be relate to the

pathophysiology of obesity. We therefore, investigated if MAOAu-VNTR, MAOA

T941G and COMT Val158Met polymorphisms contribute to the risk of increase

food intake and consequent obesity in Brazilian children.

2. Materials and Methods

Subjects

This study is a cross-sectional examination of children who had participated in a

randomised trial that occurred during their first year of life. The sample consisted of

354 children from three to four years of age. The 24-hour diet recall, carried out by

Nutrition students, recorded the child’s food intake on the day before the last home

visit. The blood samples were collected in São Leopoldo and analysed in the

Clinical Analysis Laboratory of the Cardiology Institute of Porto Alegre. Race or

ethnicity was self-defined by skin colour (i.e., whites and non-whites) as officially

used in demographic censuses in Brazil. More details of the traits studied are

described in Vitolo et al., 2008 [25]. All eligible mothers were informed by

fieldworkers about both the overall aims of the study (advice on feeding of infants

and its effects on the child's health) as well as all research procedures, including

the use of a questionnaire, anthropometric and blood haemoglobin measurements,

dental examinations and differences between the intervention and control groups.

The study protocol was approved by the Ethics Committee of the Universidade

Federal de Ciências da Saúde de Porto Alegre, and all participants provided

written informed consent before commencing the study.

Nutritional status assessed at 3-4 years old

The child’s nutritional status was assessed by means of anthropometric

measures in all visits. Weight was assessed using a portable digital scale and

height was assessed using a portable stadiometer. Their nutritional status was

estimated using the body mass index (BMI) for age charts from the International

Child Growth Standards released by the World Health Organization [26]. The waist

circumference was measured at the minimum circumference between the iliac

crest and the rib cage using an inflexible measuring tape. Triceps skinfold and

subscapular skinfold were measured using a Lange skinfold caliper to the nearest

1.0 mm. Each skinfold was measured two times on the right side of the body and

was analysed as z-score according to Multicentre Growth Study standard charts

[26].

Dietary data assessed at 3-4 years old

Two 24-hour dietary recalls were collected for each child on two randomly

selected days. A food portion measurement aid and the common household

measures (eg, teaspoons, tablespoons, cups) were used to quantify portion sizes.

Dietary information was entered into the Nutrition Support Program software

from the Escola Paulista de Medicina, Federal University of São Paulo, based on

United States Department of Agriculture (USDA) chemical composition tables. The

energy intake was calculated using the average of two diet recalls. We considered

high sugar density food (HSD) if the percentage of simple carbohydrates in 100

grams was higher than 50% and high lipid density food (HLD) if greater than 30%

fat per 100 grams. The calories provided by those foods groups were studied

separately, for statistical analysis.

DNA analyses

Genomic DNA was extracted from peripheral blood leukocytes by the Lahiri

and Nurnberger procedure [27]. MAOA MAOAu-VNTR polymorphism was

genotyped using polymerase chain reaction (PCR). The primer sequences were as

follows: forward 5’- ACAGCCTGACCGTGGAGAAG - 3 and reverse 5’-

GAACGGACGCTCCATTCGGA -3’. The PCR products containing the tandem

repeat polymorphism were resolved by electrophoresis on 6% poliacrylamide gel

with ethidium bromide. The primers used yielded 291, 321, 336, 351 and 381 base

pair (bp) fragments corresponding to the 2-, 3-, 3.5-, 4-and 5-repeat alleles,

respectively. They were then visualized under U.V light to determine the fragment

sizes by comparison with a 100 bp DNA ladder. The MAOA T941G (rs6323)

polymorphism was detected by PCR-RFLP analysis, using same primers sequence

and conditions previously described by Tádic et al., 2003 [28]. Sequences of

primers were: forward 5’- GACCTTGACTGCCAAGAT -3’ and the reverse 5’-

CTTCTTCTTCCAGAAGGCC -3’. The PCR products were digested with FnuIV

restriction enzyme according to the manufacturer’s instructions. Genotypes were

determined after electrophoresis on agarose gel 1.5%, stained with ethidium

bromide. COMT Val108/158Met (rs4680) polymorphism was detected by PCR-

RFLP analysis. Sequences of primers were: forward 5’ –

TCGTGGACGCCGTGATTCAGG - 3’ and the reverse 5’ –

AGGTCTGACAACGGGTCAGGC - 3’. The PCR products were digested with

NlaIII restriction enzyme according to the manufacturer’s instructions. Genotypes

were determined after electrophoresis on poliacrylamide gel 7%, stained with

ethidium bromide.

Statistical analyses Allele frequencies were estimated by gene counting. A χ² test for goodness

of fit was used to determine whether observed genotype frequencies distribution

agreed with those expected under Hardy-Weinberg equilibrium. For MAOA

polymorphisms the association analyses were performed separately in boys and

girls, because de MAOA gene is located in X chromosome. Kilocalories mean or

median of food clusters intake (HSD and HLD) and total/day energy and

anthropometric parameters (Waist circumference, Z-score of skinfolds of triceps

and Z-score of skinfolds of subescapular were compared among carriers of the

different genotypes by one-way analyses of variance (ANOVA) or Kruskal Wallis,

depending on variables distribution. All tests and transformations were performed

using the Statistical Package for Social Sciences Version 16.0 (SPSS®, Chicago,

IL, USA).

3. Results

The mean age of the children in this study was 4.075 0.948 years age (mean

SD), 41.7% of children were white and the percentage of boys in the sample was

57.2%. The genotype frequencies distributions observed for polymorphisms studied did

not reveal statistically significant differences compared to those expected under Hardy–

Weinberg equilibrium, for MAOAu-VNTR polymorphism in girls (χ² = 0.546, 2DF, p =

0.761); for MAOA T941G polymorphism in the girls (χ² = 0.405, 2DF, p = 0.817); for

COMT Val158Met polymorphism (χ² =0.027, 2DF, p = 0.9866). The allele and genotype

frequencies for three polymorphisms studied are presented in Table 1. Were not

detected statistically significant differences in genotype frequency distributions of

polymorphisms analyzed between white and non-white samples (data not show). In the

boy’s sample, the MAOAu-long allele presence was associated with higher intake of

HLD (median: 134.975kcal [interquartile range: 26.437–270.162]) when compared with

MAOAu-short allele (60.1kcal [0.000–192.31]; p = 0.009; Table 2); the HSD intake was

also higher in boys carriers of MAOAu-long allele (100.455kcal [54.406–163.325]) when

compared with MAOAu-short allele carriers (80.015kcal [37.45–127.115]; p = 0.034;

Table 2). In the girl’s sample, MAOAu-VNTR polymorphism was not associated with

food intake and anthropometric data (Table 3). The MAOA T941G polymorphism was

not associated with food intake and anthropometric data when analyzed in boys and

girls (Table 2 and 3). The COMT 158Val allele was associated with higher intake HLD

when compared with COMT 158Met homozygous (p = 0.008), the medians were

133.79kcal [44.23–265.80] and 83.37kcal [0.00–252.95], respectively (Table 4).

4. Discussion

There is increasing evidence for a role of the dopaminergic pathway in the

development of obesity. Food rewards and their associated stimuli both elevate

dopamine levels in crucial components of brain reward circuits [29]. In fact, food

might be the most important natural stimulus for the reward system in the brain

[30]. Small et al. [31] suggest that the amount of released dopamine (DA)

correlates with the degree of experienced pleasure. Individual differences in reward

sensitivity have been implicated in food intake. In this work, we evaluate

polymorphisms in genes of enzymes that affect dopamine availability; together

MAOA and COMT determine a part of DA available at the synapse. MAOA and

COMT are affecting both the degradation of norepinephrine and dopamine, a

decrease in activity of the gene product will increase the after-effects of these

neurotransmitter receptors. In this context, it is interesting that re-uptake inhibition

on these two systems, that will tend to have the same effect, is an effective way to

produce a weight loss in humans [32, 22].

Some studies have shown that the presence of the long allele of MAOA-u

VNTR polymorphism is associated with high MAOA activity and this phenomenon

might results in lower levels of DA in pre synaptic neuron [33, 34]. No studies have

quantified the effect of low or high activity isoforms on the availability of DA,

however, has been shown that women with one copy of high activity MAOA allele

(long allele) have higher levels of homovanillic acid (HVA), the main metabolite of

DA [35]. This finding implies that those who have a high activity MAOA allele have

increased metabolism DA and, consequently, might lead to overcompensatory

palatable food intake. In this study, our results demonstrated that MAOA u-VNTR

polymorphism was associated with amount of palatable food intake in boys

sample, boys with high activity allele (long allele) intake more HSD and HLD foods

than them with low activity allele (short allele). This polymorphism was not

associated with anthropometrical parameters in our study, probably because the

children are little and their time of exposure to obesogenic environment was not

enough, however, this food intake behaviour might confer increased risk of

developing obesity in future. Evidences obtained from studies with humans and

animal models indicating the importance of dopaminergic function in the

development of obesity are divided about the direction of causal association. One

argument is that a Reward Deficiency Syndrome (RDS) is the risk factor, while

others contend that hyper-sensitivity to reward enhances the motivation for

pleasurable activities like eating. Most studies that evaluated the polymorphisms in

the MAOA goes toward that hyper-sensitivity to reward, like in a transmission

disequilibrium test, the low activity allele of this same polymorphism was shown to

be preferentially transmitted to obese offspring of parents [34]. In addition, Visentin

et al. 2004 [33] compared the activity MAOA fat in obese and nonobese patients,

and found that the levels were halved in the obese. However, several studies will

prove that RDS is implicated in the genesis of obesity support our results, such as

the study by Wang et al. 2001 which found that the availability of dopamine D2

receptor was decreased in obese individuals in proportion to their BMI. Dopamine

modulates motivation and reward circuits and hence dopamine deficiency in obese

individuals may perpetuate pathological eating as a means to compensate for

decreased activation of these circuits.

The MAOA T941G polymorphism showed no association with

anthropometrics data or food intake of children among three to four years. This

SNP is located in the third base of a codon and does not affect the amino acid

sequence. However, Hotamisligil and Breakefield, 1991 [16] reported an

association of the 941T allele with lower MAOA enzyme activity in 40 cell lines of

known MAOA activity. When the sample was divided into two groups on the basis

of lower versus higher MAOA activity, the less common 941G, present in 25% of

the cell lines, was over-represented in the higher activity group. Functional

differences can be caused by other polymorphisms that are in disequilibrium with

the T941G variant. Gade et al., 1998 [36] recently reported MAOA gene VNTR

allele groups being associated with behavioral phenotypes in drug abusers and

patients suffering from Tourette syndrome. In this study, the longest alleles were

associated with the greatest phenotypic effect. The authors also examined the

T941G polymorphism in the patient group and found a linkage disequilibrium

between the VNTR polymorphism and the T941G polymorphism. Gade et al.

postulated that the gene variants with the higher number of repeats would be less

active than the shorter variants, which would, in respect to the function of the

T941G allele variant, be in accordance with the report of Hotamisligil and

Breakfield [16] mentioned above. Few studies have evaluated this polymorphism

and most of the time were studies that analyzed this variant only making it difficult

to evaluate a possible linkage disequilibrium with other variants.

COMT is an extracellular enzyme that O-methylates DA, and is the only

enzyme that can act on the extracellular DA. This O-methylation may occur before

or after deamination by MAO. The Met allele of COMT Val158Met polymorphism

produces a labile protein, with activity significantly lower [22, 25], thus conferring

slow detoxification of neurotransmitters [30], such as the degradation and

inactivation of dopamine [22, 30] resulting in higher levels of dopamine. Individuals

with genotype Met/Met have a reduction of 3 to 4 times the activity of enzymatic

degradation in comparison with homozigotes Val/Val; heterozygotes have an

intermediate activity [37]. We found an association between the Val allele and

more HSD and HLD food (palatable food) intake, conferring increased risk of

developing obesity which is consistent with the suggested role of COMT

Val158Met polymorphisms in obesity [20]. Further study corroborate a our results

a showing the exercise-induced weight loss in women to be slightly smaller in met

carriers [38]; in contrast, Need et col., 2006 assessing the possible association

between the COMT Val158Met polymorphism and BMI did not find any such

relationship [39]. In a study by Happonen et al., 2006 [40], no marked effects of the

COMT val158-met polymorphism on waist-hip ratio (WHR) were found. While

Annerbrink et. col., 2008 found that subjects homozygous for the low-activity allele

(Met) displayed higher WHR and abdominal sagittal diameter as compared with

heterozygous and homozygous for the high-activity allele (Val). Our results also

implied that genotypes of MAOAu-VNTR and COMT Val158Met migth have an

impact on the food intake and possibly about development of obesity. The present

and potential discrepancies between studies underline the continuing challenges of

studies with different populations with different characteristics and

pathophysiological and life-style related characteristics that may modify the effects

of the examined gene variants.

Our results indicate that is evidence that dopamine levels are associated

with feeding behavior respecting that same significant associations, in the same

direction were observed for both low activity variants of the MAOA and COMT

genes. These results therefore strongly suggest a role of heritable variation in DA

metabolism in risk with higher intake of palatable food, resulting in increased risk of

developing obesity and underscore the need for additional research in order to

replicate the results and to identify the complex interplay between the examined

psychophysiological genes that may further characterize their functionality in

feeding behavior.

An inherent limitation to our study is the moderate sample size, which may

not have enough power to detect an association of polymorphisms with small

effects on food intake and anthropometric measurements, such as MAOA T941G.

However, we believe the size of our sample was sufficient to detect relatively large

genetic effects, reinforcing the importance of our findings relating MAOA-u VNTR

polymorphism with higher intake of HLD and HSD foods and COMT Val158Met

polymorphism with higher intake of HLD foods. The results of this should be

considered with caution and should be confirmed in a larger study. It is now

important to point out another detail that is relevant to our results: the observation

that a non-association with phenotypes related to obesity anthropometric may be

due to the fact that children are small and their time of exposure to an obesogenic

environment was not enough to offset the excessive weight gain. We believe that a

follow-up to this sample may provide interesting results for the future.

Conflict of interest statement

The authors have declared no conflict of interest.

5. References

[1] James PT, Leach R, Kalamara E, Shayeghi M. The worldwide obesity epidemic.

Obes Res 2001; 9: 228S–33S

[2] Maes HH, Neale MC, Eaves LJ. Genetic and environmental factors in relative

body weight and human adiposity. Behav Genet 1997; 27: 325–351.

[3] Schachter S, Goldman R, Gordon A. Effects of fear, food deprivation, and obesity on

eating. J Pers Soc Psychol 1968; 10: 91–97.

[4] Stunkard AJ, Fox S. The relationship of gastric motility and hunger. A summary of

the evidence. Psychosom Med 1971; 33: 123–134.

[5] Nisbett RE. Taste, deprivation, and weight determinants of eating behavior. J Pers

Soc Psychol 1968; 10: 107–116.

[6] Jansen A, Theunissen N, Slechten K, et al. Overweight children overeat after

exposure to food cues. Eat Behav 2003; 4: 197–209.

[7] Johnson SL, Birch LL. Parents’ and children’s adiposity and eating style. Pediatrics

1994; 94: 653– 661.

[8] Birch LL, Fisher JO. Mothers’ child-feeding practices influence daughters’ eating and

weight. Am J Clin Nutr 2000; 71: 1054–1061.

[9] Braet C, Van Strien T. Assessment of emotional, externally induced and restrained

eating behaviour in nine to twelve-year-old obese and nonobese children. Behav Res

Ther 1997; 35: 863–873.

[10] Hoebel BG. Brain neurotransmitters in food and drug reward. Am J Clin Nutr 1985;

42: 1133-1150.

[11] Parada MA, Hernandez L, Puig De, Parada M, et al. Dopamine in the lateral

hypothalamus may be involved in the inhibition of locomotion related to food and water

seeking. Brain Res. Bull. 1990, 25: 961–968.

[12] Doss FW. The effects of antipsychotic drugs on body weight: a retrospective

review. J. Clin. Psychiatry. 1979; 40: 528 –530.

[13] Fuemmeler BF, Agurs-Collins TD, McClernon FJ, et al. Genes implicated in

serotonergic and dopaminergic functioning predict BMI categories. Obesity (Silver

Spring) 2008; 16: 348-355.

[14] Gelernter J, Crowe RR. Candidate genes and psychiatric genetics: Tomorrow

never knows. Psychiatr. Ann. 1997; 27: 262–267.

[15] Bach AW, Lan NC, Johnson DL., et al. cDNA cloning of human liver monoamine

oxidase A and B: molecular basis of differences in enzymatic properties. Proc. Natl.

Acad. Sci. U. S. A. 1988; 85: 4934–4938.

[16] Hotamisligil GS, Breakefield XO: Human monoamine oxidase A gene determines

levels of enzyme activity. Am J Hum Genet 1991; 49: 383-392.

[17] Sabol SZ, Hu S, Hamer D. A functional polymorphism in the monoamine oxidase A

gene promoter. Hum Genet 1998; 103: 273– 279.

[18] Deckert J, Catalano M, Syagailo YV, et al. Excess of high activity monoamine

oxidase A gene promoter alleles in female patients with panic disorder. Hum Mol Genet

1999; 8: 621–624.

[19] Annerbrink K, Westberg L, Nilsson S, et al. Catechol O-methyltransferase val158-

met polymorphism is associated with abdominal obesity and blood pressure in men.

Metabolism 2008; 57: 708-711.

[20] Kring SII, Werge T, Holst C, et al. Polymorphisms of Serotonin Receptor 2A and 2C

Genes and COMT in Relation to Obesity and Type 2 Diabetes. PLoS ONE 2009; 4:

e6696.

[21] Wang GJ, Volkow ND, Logan J, et al. Brain dopamine and obesity. Lancet 2001;

357/9253: 354–357.

[22] Männisto PT, Kaakkola S. Catechol-O-methyltransferase (COMT): biochemistry,

molecular biology, pharmacology, and clinical efficacy of the new selective COMT

inhibitors. Pharmacol Revs 1999; 51: 593–628.

[23] Lundström K, Salminen M, Jalanko A, et al. Cloning, expression and structure of

catechol-O-methyltransferase. Biochim. Biophys. Acta 1995; 1251: 1–10.

[24] Strous RD, Nolan KA, Lapidus R, et al. Aggressive behavior in schizophrenia is

associated with the low enzyme activity COMT polymorphism: a replication study. Am J

Med Genet 2003; 120B: 29–34.

[25] Vitolo MR, Bortolini GA, Dal Bó Campagnolo P, et al. Effectiveness of a nutrition

program in reducing symptoms of respiratory morbidity in children: A randomized field

trial. Prev. Med. 2008; 47: 384-388.

[26] WHO. World Health Organization. The WHO Child Growth Standards, 2006.

Available at http://www.who.int/childgrowth/standards/en/.

[27] Lahiri DK, Nurnberger JI Jr. A rapid non-enzymatic method for the preparation of

HMW DNA from blood for RFLP studies. Nucleic Acids Res 1991; 19: 5444.

[28] Tádic A, Rujescu D, Szegedi A, et al. Association of a MAOA gene variant with

generalized anxiety disorder, but not with panic disorder or major depression. Am J Med

Genet B Neuropsychiatr Genet. 2003; 117: 1-6.

[29] Bassareo, V., Di Chiara, G. Differential influence of associative and nonassociative

learning mechanisms on the responsiveness of prefrontal and accumbal dopamine

transmission to food stimuli in rats fed ad libitum. J Neurosci 1997; 17: 851-861.

[30] Davis, CA, Levitan, R.D, Kaplan, AS, et al. Reward sensitivity and the D2 dopamine

receptor gene: A case-control study of binge eating disorder. Prog

Neuropsychopharmacol Biol Psychiatry 2008; 32: 620-628.

[31] Small, D. M., Jones-Gotman, M., Dagher, A. Feeding-induced dopamine release in

dorsal striatum correlates with meal pleasantness ratings in healthy human volunteers.

Neuroimage 2003; 19: 1709-1715.

[32] Astrup A, Meier DH, Mikkelsen BO, et al. Weight loss produced by tesofensine in

patients with Parkinson’s or Alzheimer’s disease. Obesity (Silver Spring) 2008; 16/6:

1363–1369.

[33] Visentin V, Prevot D, De SF, et al. Alteration of amine oxidase activity in the

adipose tissue of obese subjects. Obes Res 2004; 12: 547–555.

[34] Camarena B, Santiago H, Aguilar A, et al. Family-based association study between

the monoamine oxidase A gene and obesity: implications for psychopharmacogenetic

studies. Neuropsychobiology 2004; 49, 126–129.

[35] Lohmueller KE, Pearce CL, Pike M, et al. Meta-analysis of genetic association

studies supports a contribution of common variants to susceptibility to common disease.

Nat Genet 2003 33: 177–182.

[36] Gade R, Muhleman D, Blake H, et al. Correlation of length of VNTR alleles at the

Xlinked MAOA gene and phenotypic effect in Tourette syndrome and drug abuse. Mol

Psychiatry 1998; 3: 50–60.

[37] Lachman HM, Papolos DF, Saito T, et al. Human catechol-o-methyltransferase

pharmacogenetics: description of a functional polymorphism and its potential application

to neuropsychiatric disorders. Pharmacogenetics 1996; 6: 243−250.

[38] Tworoger SS, Chubak J, Aiello EJ, Yasui et al. The effect of CYP19 and COMT

polymorphisms on exercise-induced fat loss in postmenopausal women. Obesity

Research 2004; 12: 972-981.

[39] Need AC, Ahmadi KR, Spector TD, Goldstein DB. Obesity is associated with

genetic variants that alter dopamine availability. Ann Hum Genet 2006; 70: 293-303.

[40] Happonen P, Voutilainen S, Tuomainen TP, Salonen JT. Catechol-

omethyltransferase gene polymorphism modifies the effect of coffee intake on incidence

of acute coronary events. PLoS ONE 2006; 1: e117.

Table 1

Distributions of the MAOA-u VNTR, MAOA T941G and COMT Val158Met polymorphisms

alleles and genotype frequencies in children from three to four years of age.

MAOA-u VNTR Boys (186) Girls (139)

Alelle/genotype Frequency (n) Frequency (n)

Long allele 0.655 (122) 0.641 (119)

Long/Long - 0.428 (59)

Long/Short - 0.428 (60)

Short/Short - 0.144 (20)

MAOA T941G Boys (186) Girls (139)

Alelle/genotype Frequency (n) Frequency (n)

G allele 0.207 (39) 0.213 (55)

G/G - 0.036 (5)

G/T - 0.359 (50)

T/T - 0.605 (84)

COMT Val158Met n=326

Alelle/genotype Frequency (n)

Met allele 0.615 (278)

Met/Met 0.377 (123)

Val/Met 0.475 (155)

Val/Val 0.148 (48)

n = individuals number carrier allele/genotype

Table 2

Food intake and anthropometric data according MAOA-u VNTR and MAOA T941G polymorphisms genotypes in boys from

three to four years of age.

Food intake

MAOA-u VNTR Long allele N Short allele N p

HSD (kcal) 100.45 [54.40–163.32] a 120 80.01 [37.45–127.11] a 63 0.034b

HLD (kcal) 134.97 [26.43–270.16] a 120 60.10 [0.00–192.31] a 63 0.009b

Average energy intake daily (kcal) 1544.49389.73c 120 1512.37423.94c 63 0.608d

T941G G allele N T allele N p

HSD (kcal) 82.307kcal [40.75– 128.10] a 38 97.15kcal [49.43–159.47] a 145 0.105b

HLD (kcal) 53.23kcal [0.00– 228.19] a 38 127.71kcal [20.58–256.50] a 145 0.154b

Average energy intake daily (kcal) 1545.58430.21c 38 1530.25394.45c 145 0.834d

Anthropometric data

MAOA-u VNTR Long allele N Short allele N p

BMI Z-score 0.161.19c 122 0.361.12c 63 0.271 d

Waist circumference in cm 50.65 3.53c 122 51.55 3.42c 63 0.099 d

Z-score of skinfolds of triceps 7.372.46c 122 7.85 2.46c 63 0.207 d

Z-score of skinfolds of subescapular 5.362.45c 122 5.792.38c 63 0.261 d

T941G G allele N T allele N p

BMI Z-score 0.521.16c 38 0.161.16c 147 0.086 d

Waist circumference in cm 51.773.67c 38 50.753.45c 147 0.110d

Z-score of skinfolds of triceps 8.032.66c 38 7.402.40c 147 0.160d

Z-score of skinfolds of subescapular 5.812.78c 38 5.432.33c 147 0.391d

HSD indicates high sugar density foods; HLD indicates high lipid density foods; BMI indicates Body Mass Index; a Median

[Interquartile Range]; b Mann-Whitney U; c Mean standard deviation, d Test T for independent sample.

n = individuals number carrier genotype

Table 3

Food intake and anthropometric data according MAOA-u VNTR and MAOA T941G polymorphisms genotypes in girls from

three to four years of age.

Food intake

MAOA-u VNTR Long/Long N Long/Short N Short/Short N p

HSD (kcal) 97.62 [44.70–144.74] a 57 100.66 [28.06–169.45] a 58 151.68 [41.69–199.26a] 20 0.318b

HLD (kcal) 106.84 [47.73–282.79] a 57 146.31 [37.25–271.34] a 58 98.67 [0.00–254.53] a 20 0.671b

Average energy intake daily(kcal) 1472.04406.36c 57 1543.14434.21c 58 1406.79235.16c 20 0.370d

T941G G/G N G/T N T/T N p

HSD (kcal) 139.37 [56.81–203.52] a 5 108.80 [39.14–173.46] a 49 94.75 [36.95–154.27] a 81 0.586b

HLD (kcal) 253.60 [15.67–303.82] a 5 122.11 [46.88– 247.55] a 49 106.84 [20.77–282.79] a 81 0.265b

Average energy intake daily (kcal) 1308.26214.69c 5 1477.26402.75c 49 1513.79405.83c 81 0.509d

Anthropometric data

MAOA-u VNTR Long/Long N Long/Short N Short/Short N p

BMI Z-score 0.240.97c 58 0.391.12c 59 0.120.98c 20 0.537 d

Waist circumference(cm) 50.40 3.04c 58 51.234.37c 59 50.323.24c 20 0.412 d

Z-score of triceps skin folds 7.842.12c 58 8.012.34c 59 7.672.32c 20 0.822 d

Z-score of subescapular skin folds 6.291.84c 58 6.502.82c 59 5.752.14c 20 0.537 d

T941G G/G N G/T N T/T N p

BMI Z-score -0.03 0.82c 5 0.271.15c 49 0.310.98c 83 0.269 d

Waist circumference(cm) 50.602.07c 5 51.074.21c 49 50.573.46c 83 0.282d

Z-score of triceps skin folds 6.901.24c 5 7.732.32c 49 8.042.22c 83 0.813d

Z-score of subescapular skin folds 4.901.02c 5 6.342.98c 49 6.361.94c 83 0.922d

HSD indicates high sugar density foods; HLD indicates high lipid density foods; BMI indicates Body Mass Index; a Median

[Interquartile Range]; b Kruskal Wallis Test; c Mean standard deviation, d One-Way ANOVA.

n = individuals number carrier genotype

Table 4

Food intake and anthropometric data according COMT Val158Met polymorphism genotype in children from three to four

years of age.

Food Intake

Non carriers n Carries Val n p

HSD (kcal) 88.25 [43.65–138.14a] 120 101.64 [42.35–168.61] a 198 0.154b

HLD(kcal) 83.37 [0.00–252.95] a 120 133.79 [44.23–265.80] a 198 0.008 b

Average energy intake daily (kcal) 1501.93424.77c 120 1524.90385.27c 198 0.620 d

Anthropometric data

IMC Z-score 0.311.16c 121 0.221.08c 202 0.518 d

Waist circumference(cm) 51.767.23c 122 50.853.59c 203 0.132 d

Z-score of triceps skin folds 7.752.68c 120 7.682.21c 203 0.814 d

Z-score of subescapular skin folds 5.882.69c 120 5.852.27c 203 0.905 d

HSD indicates high sugar density foods; HLD indicates high lipid density foods; BMI indicates Body Mass Index; a Median

[Interquartile Range]; b Mann-Whitney U; c Mean standard deviation, d Test T for independent sample.

n = individuals number carrier genotype

CAPÍTULO 5

ANEXOS

ANEXO A - PARECER DO COMITÊ DE ÉTICA EM PESQUISA DA UFCSPA

ANEXO B – TERMO DE CONSENTIMENTO INFORMADO

TERMO DE CONSENTIMENTO INFORMADO

O presente estudo (Investigação dos Fatores de Risco para Obesidade Precoce e Anemia

em uma Coorte de Crianças Submetidas a um Programa de Intervenção Nutricional no Primeiro

Ano de Vida) pretende dar continuidade ao trabalho realizado no 1º ano de vida de seu filho, visando

acompanhar as condições de crescimento e desenvolvimento por meio das medidas de peso, altura,

quantidade de gordura corporal, as quais não conferem riscos nem dor para seu filho. Utilizaremos um

questionário para fazer-lhe perguntas sobre sua família, o qual conterá: condições de vida (sociais e

econômicas), moradia, práticas alimentares de seu filho, atividades diárias e presença de doenças. Em

data marcada com o pesquisador, será verificada a pressão arterial e será realizada coleta de sangue

por profissional treinado com agulhas descartáveis, sem risco de contaminação, para análise dos níveis

de colesterol, LDL, triglicerídeos, proteína-C reativa e glicemia, além disso, será avaliado alterações

genéticas que podem estar associadas à obesidade e anemia. A criança sentirá um pequeno

desconforto o momento da picada, porém não haverá riscos a sua saúde. Entretanto, não há outra

forma de verificação que possa fornecer resultados mais precisos. Essas informações serão

transformadas em números e a identidade da sua família não será divulgada em nenhum momento.

Este estudo é importante para se conhecer os fatores que são responsáveis pela obesidade e anemia

na infância e dessa forma intervir de forma mais ampla na população. A senhora receberá todos os

resultados das avaliações e orientações ou encaminhamentos se necessário para o melhor bem estar

seu e de seu filho. A senhora também terá toda a liberdade de interromper a entrevista em qualquer

momento ou de pedir maiores esclarecimentos caso tenha alguma dúvida. Assinará 2 cópias

desse consentimento, ficando 1 em seu poder e outra com a responsável do programa.

São Leopoldo, ____ de _____________________ de 200___.

Nome_____________________________________________________________

Assinatura__________________________________________________________

Tel Prof. Márcia Regina Vitolo – tel 81629929 – 32248822 (ramal 153)

Termo de Consentimento Informado ao Paciente

Eu, Profa. Márcia Regina Vitolo, nutricionista, estou realizando a pesquisa: “INCIDÊNCIA DE

OBESIDADE E ANEMIA EM UMA COORTE DE NASCIMENTO ACOMPANHADA ATÉ 4 ANOS

DE IDADE: AVALIAÇÃO DO COMPONENTE GENÉTICO”. Esta pesquisa visa esclarecer como

variações genéticas normais podem influenciar no desenvolvimento da obesidade infantil, assim como,

no desenvolvimento de anemia. Para que tal pesquisa possa ser realizada peço sua colaboração,

autorizando que seja realizado o estudo das variantes genéticas nas amostras de sangue que já foram

coletadas de seu filho.

Quais os riscos em participar? Como não se fará nenhuma picada a mais do que aquelas

necessárias para os exames que já foram realizados não há risco para a paciente em participar deste

projeto.

O que o paciente ganha com este estudo?

Com a análise, poderemos saber quais crianças podem ter maior predisposição ao desenvolvimento de

obesidade e anemia. No entanto, os benefícios deste estudo poderão ser obtidos apenas em longo

prazo.

Quais são os seus direitos?

Seus registros médicos serão sempre tratados confidencialmente. Os resultados deste estudo poderão

ser usados para fins científicos, mas você não será identificado por nome. Sua participação no

estudo é voluntária, de forma que, caso você decida não participar, isto não afetará no tratamento normal

que você tem direito.

Assinará 2 cópias desse consentimento, ficando 1 em seu poder e outra com a responsável do

programa.

Nome : _________________________________________________________

Assinatura:_______________________________________________________

Núm de identificação:____________________

Assinantura do responsável:__________________________________________

Data: ___/___/______

Em caso de qualquer dúvida quanto à pesquisa ou sobre os seus direitos, você poderá contatar com

Prof. Márcia Regina Vitolo – tel 81629929 – 32248822 (ramal 153)

ANEXO C – QUESTIONÁRIO

Projeto: Investigação dos Fatores de Risco para Obesidade Precoce e Anemia

em uma Coorte de Crianças que Foram Submetidas a um Programa de

Intervenção Nutricional no Primeiro Ano de Vida

FICHA DA CRIANÇA

Entrevistador________________________________________________________

1. Data _____/_____/_____ Data4: ___/___/__

Identificação (criança):

2.Telefones para contato____________________________________________

3.Numero de identificação ________________

4.Nome da criança__________________________________

5.Nome da mãe_____________________________________

6.Endereço: ___________________________________________

_____________________________________________________

_____________________________________________________

_____________________________________________________

7.Data de Nascimento: _____/_____/_____

Ident4: ________

Dados Maternos e Socioeconômicos:

8.Qual a sua idade? __________anos

09.Data de nascimento da mãe ____/____/_____

10.Qual o seu estado civil?

Casada/ou mora junto (1) Viúva (2) Solteira (3) Separada (4)

11.Você teve outros filhos?

(1) Sim (2) Não (pule para a questão 14)

12. Se sim:

Quantos:__________

DN____/____/_____

DN____/____/____-

DN____/____/____

13.Quantas pessoas moram na sua casa? __________

14.Qual o grau de parentesco?

(1) Família nuclear

(2) Família não nuclear

IdMae4:________

DNm4_________

EstCivil4 ______

Filhos4 _______

Quant4:_______

DNf1:___/___/___

DNf2___/___/___

DNf3___/___/___

Famí4:_______

Adul4:_______

Parente4 _____

15.Qual a sua ocupação?

(1) Desempregada (2) Empregada c/ carteira assinada (3)

Empregada s/ carteira assinada (4) Do lar (5) Estudante

16.Qual a ocupação do pai do seu (sua) filho (a)? (1)

Desempregado (2) Empregado c/ carteira assinada (3) Empregado

s/ carteira assinada (4) Aposentado (5) Estudante

17.Qual a renda total da família? R$ ______________

OcupaMae4:____

OcupaPai4:_____

RendaT4:______

18.Qual o gasto familiar mensal com alimentação? R$______

19.Qual o gasto familiar mensal com transporte? R$______

GFA:__________

GFT: _________

20.Você é fumante?

(1) Sim (2) Não (pule para a 22) (3) Parou de fumar (pule para a 22)

Vcfum4:_______

21.Quantos cigarros você fuma por dia? _______ Ncd4:______

22.Alguém que mora na sua casa é fumante?

Sim (1) Não (2) (Pule para a pergunta 24)

Ncd4:______

Se sim:

23.Quem é fumante na sua casa?

Pai (1) Outros moradores da casa (2) Anotar quantos (3)Pai e outros

QuemFuma: ______

24.Você fumou durante a gestação do seu filho que participou do

projeto?

(1) Sim (2) Não (pule para a 26)

Fgest4:________

Se sim:

25.Quantos cigarros você fumava por dia?____________________ Ncfum4______

26. Alguém na família tem ou teve? (referente a criança)

Para a pergunta quem: coloque 1 quando sim e 2 quando não

26.a Obesidade: (1) Sim (2) Não ou (3) Não Sabe (9) IGN

Obesi: ____

Obpai: ___

Obmãe: ___

Se sim:Quem? ( ) Pai ( ) Mãe ( ) Avós ( ) Tios

( )Irmãos (88) NSA (99) IGN

26.b Colesterol Alto: (1) Sim (2) Não ou (3) Não Sabe (9) IGN

Se sim:Quem?( ) Pai ( ) Mãe ( ) Avós ( ) Tios

( )Irmãos (88)NSA (99) IGN

26.c Doença cardiovascular: (1) Sim (2) Não (3) Não Sabe (9) IGN

Se sim:Quem?( ) Pai ( ) Mãe ( ) Avós ( ) Tios

( )Irmãos (88)NSA (99) IGN

26.d Diabetes Melitus: (1) Sim (2) Não ou (3) Não Sabe) (9) IGN

Se sim:Quem?( ) Pai ( ) Mãe ( ) Avós ( ) Tios

( )Irmãos (88)NSA (99) IGN

Obavós: ___

Obatio: ___

Obairm: ___

ColAlto: ____

Colpai: _____

Colmãe: ____

Colavós: ____

Colatio: _____

Colairm: _____

DCV: ____

DCVpai: ___

DCVmãe: ___

DCVavós: ___

DCVtio: ___

DCVirm: ___

DM: ____

DMpai:___

DMmãe:___

DMavós:___

DMtio:___

DMirm:___

26.e Hipertensão (Pressão Alta):(1) Sim (2) Não (3) Não Sabe

(9) IGN

Se sim:Quem?( ) Pai ( ) Mãe ( ) Avós ( ) Tios

( )Irmãos (88)NSA (99) IGN

PA: _____

PApai: ___

PAmãe:____

PAavós:____

PAtio:____

PAirm:____

27. A criança realizou algum exame de sangue após o realizado quando

o seu filho estava com 1 ano de idade, através do nosso projeto?

Sim (1) Não (2)

Exam4________

Se sim anotar:

Data:___/___/___ Data:___/___/___

Hb:_____g/dl Hb:_____g/dl

Ht:______g/dl Ht:______g/dl

VCM:_____fl VCM:_____fl

HCM:_____pg HCM:_____pg

28. Atualmente o seu filho esta recebendo algum suplemento de ferro?

(1)Sim (2) Não

Se sim:

29.Qual o nome do suplemento?_________________________________

30.Qual a quantidade? ________gotas ou ______drágeas

31.O seu filho realmente recebe o suplemento? (1) Sim (2) nao

32.Que idade a crianca tinha quando iniciou com o uso desse

suplemento?_______meses

33. Tempo de uso:______________semanas

Suple4______

Qual4_____

Qgotas___

Qdrag____

Receb4____

Idade:____

Tempu4____

CONDIÇÕES DE SAÚDE NOS ÚLTIMOS 6 MESES

34. Seu (sua) filho (a) foi internado no últimos 6 meses?

Sim (1) Não (2) Não sabe (3)

35.Seu (sua) filho (a) teve episódios de diarréia no últimos 6 meses? Sim (1)

Não (2) Não sabe (3)

36. Seu (sua) filho (a) apresentou febre importante no últimos 6 meses? Sim

(1) Não (2) Não sabe (3)

37. Seu (sua) filho (a) teve infecção no últimos 6 meses?

Sim (1) Não (2) Não sabe (3)

38. Seu (sua) filho (a) teve infecção urinária nos últimos 6 meses?

Sim (1) Não (2) Não sabe (3)

39.O seu (sua) filho (a) apresentou algum problema respiratório?

Sim (1) Não (2) (pule para a 67)

Intern4_____

Diarré4______

Febre4_ ______

Infecç4_______

InfUri4_ _____

Resp4______

Leia as alternativas para o entrevistado

40. Qual ou quais problema (s) que seu (sua) filho (a) apresenta?

Tosse ( ) Coriza ( )

Obstrução Nasal ( ) Respiração rápida ou difícil ( )

Para o quadro ao lado preencher 1 para sim e 2 para não

Tosse4____

Coriza4____

Obstru4_____

Respd4_____

Preencher se a criança recebe leite de vaca: (se não recebe pule para a 72)

41. Qual o volume da preparação?_________________ml Vol4_________

42. Qual a freqüência que seu filho toma leite no dia? _______ vezes

43. Volume total de leite ingerido no dia: _________ml

(descontar se sobra)

freqleit_________

Volleite______

44. A criança vai a creche?

Sim (1) Não (2)

45. Período: meio turno (1) dia inteiro (2)

46 Desde que idade (em meses):______________

47.Se não, no lugar onde ela fica, tem outras crianças junto?

Sim (1) Não (2)

Creche4______

Períod4_______

temp4_______

idcre4________

ondfica4_____

48. O (a) seu (sua) filho (a) bebe água?

Sim (1) Não (2) (Pule para a pergunta 51)

Água4 _________

Se sim:

49. Quanto bebe? _____________________________________

50. Qual o “tipo” da água?

Filtrada / Fervida / Torneira tratada e fervida / Mineral

(próprias para o consumo) (1)

Torneira não tratada (impróprias para o consumo) (2)

51. Seu (sua) filho (a) comeu/come terra ou objetos não alimentares?

Sim (1) Não (2) (pule para a 80) Não sabe (3) (pule para a 53)

Quant4________

Tagua4 _______

Objet4 ______

Se sim:

52. Quais os objetos não alimentares que seu (sua) filho (a) comeu?

(1) Terra (2) Sabão/Sabonete (3) Terra + sabão (5) casca da

mandioca (4) Outras substancias _____________________(qual?)

Quais4________

Estado Nutricional:

53. Peso___________gramas

54. Comprimento________cm

Peso4_________

Compri4_______

Atividades diárias( ontem) :

55. Que horas foi dormir ontem___ Que horas acordou hoje______/

horas de sono:_____

56. O que fez ontem pela manha:

( ) Creche / Tempo______

( ) Assistiu TV / Tempo:______

( ) Brincou fora de casa / Tempo:_____

( ) Brincou dentro de casa / Tempo:_____

( ) Dormiu / Tempo:____

57. O que fez ontem de tarde:

( ) Creche / Tempo______

( ) Assistiu TV / Tempo:______

( ) Brincou fora de casa / Tempo:_____

( ) Brincou dentro de casa / Tempo:_____

( ) Dormiu / Tempo:____

58. O que fez ontem de noite:

( ) Assistiu TV / Tempo:______

( ) Brincou dentro de casa / Tempo:_____

( ) Dormiu / Tempo:____

OBS:Colocar sempre o tempo de HORAS

59. Tem alguma atividade física regular na semana:

( ) Sim ( )Não

Se sim qual:_____________________________

Freqüência na semana:_____________________

Hsonoit____

MCrecheT___

MTvT_____

MBrifT_____

MBridT____

MDormT_____

TCrecheT___

TTvT_____

TBrifT_____

TBridT____

TDormT_____

NTvT_____

NbrinT_____

NdormT_____

Ativ_____

Qual_____

60. Você considera seu filho:

1. muito calmo

2. calmo

3. ativo

4. muito ativo

5. agitado

FreqS____

ConFi_____

ANEXO D – INSTRUÇÕES BRITISH JOURNAL OF NUTRITION

Instruções para autores da Revista Britsh Journal of Nutrition a qual foi submetido o

artigo intitulado: Association of DRD2 TaqIA and -141C InsDel polymorphisms

with food intake and anthropometric data in Brazilian children.

Directions to Contributors

British Journal of Nutrition

(Revised July 2009)

The British Journal of Nutrition is an international peer-reviewed journal that publishes original papers, review articles and short

communications in all branches of nutritional science. Short communications will be expedited through the review process. The

underlying aim of all work should be, as far as possible, to develop nutritional concepts. The British Journal of Nutrition

encompasses the full spectrum of nutritional science including epidemiology, dietary surveys, nutritional requirements and

behaviour, metabolic studies, body composition, energetics, appetite, obesity, ageing, endocrinology, immunology, neuroscience,

microbiology, genetics and molecular and cell biology. The journal does not publish case studies or papers on food technology, food

science or food chemistry.

As a contributor you are asked to follow the guidelines set out below. Prospective authors may also contact the Editorial Office

directly on +44 (0)20 7605 6555 (telephone), +44 20 7602 1756 (fax) or edoffice@nutsoc.org.uk (email).

Papers submitted for publication should be written in English and be as concise as possible. If English is not the first language of

the authors then the paper should be checked by an English speaker. The British Journal of Nutrition now operates an on-line

submission and reviewing system (eJournalPress). Authors should submit to the following address: http://bjn.msubmit.net/.

Receipt of papers will be acknowledged immediately.

Papers should be accompanied by a statement of acceptance of the conditions laid down in the Directions to Contributors. The

statement should affirm that the submission represents original work that has not been published previously, that it is not currently

being considered by another journal, and that if accepted for the British Journal of Nutrition it will not be published elsewhere in the

same form, in English or in any other language, without the written consent of the Nutrition Society. It should also confirm that each

author has seen and approved the contents of the submitted manuscript. At the time of acceptance the authors should provide a

completed copy of the ‘Licence to Publish’ (in lieu of copyright transfer), which is available on the Nutrition Society’s web

pages (http://www.nutritionsociety.org); the Society no longer requires copyright of the material published in the journal, only a

„Licence to Publish.‟ The authors or their institutions retain the copyright.

The manuscript must include a statement reporting any conflicts of interest, all sources of funding and the contribution of each

author to the manuscript. This statement should be placed at the end of the text of the manuscript before the references are listed. If

there are no conflicts of interest this must be stated. If the work was funded, please state “This work was supported by (for example)

The Medical Research Council [grant number xxx (if applicable)]”. If the research was not funded by any specific project grant, state

“This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.”

This journal adheres to the Committee on Publication Ethics (COPE) guidelines on research and publications ethics

http://www.publicationethics.org.uk/guidelines .

When substantial revisions are required to manuscripts, authors are given the opportunity to do this once only; the need for any

further changes should at most reflect only minor issues. If a paper requiring revision is not resubmitted within 3 months, it may, on

resubmission, be deemed a new paper and the date of receipt altered accordingly.

The British Journal of Nutrition publishes the following: Full Papers, Short Communications, Review Articles, Systematic

Reviews, Horizons in Nutritional Science, Workshop Reports, Invited Commentaries, Letters to the Editor/Nutrition

Discussion Forums, Book Reviews, Obituaries, Notices, Announcements and Editorials.

Full Papers, Short Communications, Reviews, Systematic Reviews, Horizons Articles and Workshop Reports should be

submitted to: http://bjn.msubmit.net/. Please contact the Editorial Office on edoffice@nutsoc.org.uk regarding any other types of

article.

Short Communications. Papers submitted as Short Communications should consist of an abstract (250 words maximum), and no

more than 3000 words of text (including references). Each Short Communication can include up to two tables or one table and one

figure, but these will be at the expense of text (one half-page table or figure is equivalent to about 500 words in two columns or 250

words in one column).

A short communication should describe a complete study that examines a specific question of scientific interest and that

extends nutritional knowledge and understanding. The nature of the study or question being investigated means that the number of

experiments or the amount of data presented is less than would be expected for a full publication. However, all aspects of scientific

rigour and evaluation will be of the same standard as for a full publication.

Review Articles/Horizons in Nutritional Science. These will be handled by the Reviews Editor. Please contact the Editorial Office

with any queries regarding the submission of potential review articles.

Systematic Reviews. These will be handled by the Systematic Reviews Editor. Please contact the Editorial Office with any queries

regarding the submission of potential review articles.

Letters to the Editor/Nutrition Discussion Forum Letters are invited that discuss, criticise or develop themes put forward in papers

published in the British Journal of Nutrition or that deal with matters relevant to it. They should not, however, be used as a means of

publishing new work. Acceptance will be at the discretion of the Editorial Board, and editorial changes may be required. Wherever

possible, letters from responding authors will be included in the same issue.

Form of full papers submitted for publication. The onus of preparing a paper in a form suitable for sending to press lies with the

author. Authors are advised to consult a current issue in order to make themselves familiar with the British Journal of Nutrition as to

typographical and other conventions, layout of tables etc. Sufficient information should be given to permit repetition of the published

work by any competent reader of the British Journal of Nutrition. Authors are encouraged to consult the latest guidelines produced

by the International Committee of Medical Journal Editors (ICMJE), which contains a lot of useful generic information about

preparing scientific papers http://www.icmje.org/ and also the CONSORT guidelines for reporting results of randomised trials

http://www.consort-statement.org/ .

Authors are invited to nominate up to four potential referees who may then be asked by the Editorial Board to help review the

work.

Typescripts should be prepared with 1·5 line spacing and wide margins (2 cm), the preferred font being Times New Roman size

12. At the ends of lines words should not be hyphenated unless hyphens are to be printed. Line numbering and page numbering is

required.

Spelling should generally be that of the Concise Oxford Dictionary (1995), 9th ed. Oxford: Clarendon Press. Papers should

normally be divided into the following parts:

(a) Title page: authors‟ names should be given without titles or degrees and one forename may be given in full. The name and

address of the institution where the work was performed should be given, as well as the main address for each author.

The name and address of the author to whom correspondence should be sent should be clearly stated, together with telephone and

fax numbers and email address. Other authors should be linked to their address using superscript Arabic numerals.

Any necessary descriptive material about the authors, e.g. Beit Memorial Fellow, should appear at the end of the paper in the

Acknowledgments.

If the paper is one of a series of papers that have a common main title followed by a subtitle specific to the individual paper,

numbering should not be used to indicate the sequence of papers. The format should be „common title: specific subtitle‟, with a short

common title, e.g. Partitioning of limiting protein and energy in the growing pig: testing quantitative rules against experimental data.

The title page should also contain a shortened version of the paper‟s title, not exceeding forty-five letters and spaces in length,

suitable for use as a running title in the published paper.

Authors are asked to supply three or four key words or phrases (each containing up to three words) on the title page of the

typescript.

(b) Abstract: each paper must open with an abstract of not more than 250 words. The abstract should be a single paragraph of

continuous text outlining the aims of the work, the experimental approach taken, the principal results and the conclusions and their

relevance to nutritional science.

(c) Introduction: it is not necessary to introduce a paper with a full account of the relevant literature, but the introduction

should indicate briefly the nature of the question asked and the reasons for asking it. It should be no longer than two pages.

(d) Experimental methods: methods should appear after the introduction.

A paper describing any experimental work on human subjects must include the following statement in the materials/methods

section: “This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving

human subjects/patients were approved by the [insert name of the ethics committee; a specific ethics number may be inserted if you

wish]. Written [or Verbal] informed consent was obtained from all subjects/patients. [Where verbal consent was obtained this must

be followed by a statement such as: Verbal consent was witnessed and formally recorded].”

Experiments involving the use of vertebrate animals. The Editors will not accept papers reporting work carried out using

inhumane procedures. When reporting on experiments involving the use of vertebrate animals, authors must state whether

institutional and national guidelines for the care and use of animals were followed and that all experimental procedures involving

animals were approved by the [insert name of the ethics committee or other approving body; the authors could insert a specific

ethics/approval number following this if they wish]. Please state whether institutional and national guidelines for the care and use of

animals were followed and that all experimental procedures involving animals were approved by the [insert name of the ethics

committee or other approving body; a specific ethics/approval number can be inserted if you wish].

(e) Results: these should be given as concisely as possible, using figures or tables as appropriate.

(f) Discussion: while it is generally desirable that the presentation of the results and the discussion of their significance should

be presented separately, there may be occasions when combining these sections may be beneficial. Authors may also find that

additional or alternative sections such as „conclusions‟ may be useful. The discussion should be no longer than five pages.

(g) Acknowledgments: these should be given in a single paragraph after the discussion and include the following information:

source of funding, declaration regarding any conflicts of interest and a brief statement regarding the contribution(s) of each author. If

there are no conflicts of interest this must be stated. If the work was funded, please state “This work was supported by (for example)

The Medical Research Council [grant number xxx (if applicable)]”. If the research was not funded by any specific project grant, state

“This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.” A sentence

describing the contribution of each author should also be included.

(h) References: these should be given in the text using the Vancouver system. They should be numbered consecutively in the

order in which they first appear in the text using superscript Arabic numerals in parentheses, e.g. „The conceptual difficulty of this

approach has recently been highlighted(1,2–4)‟. If a reference is cited more than once the same number should be used each time.

References cited only in tables and figure legends and not in the text should be numbered in sequence from the last number used in

the text and in the order of mention of the individual tables and figures in the text. At the end of the paper, on a page(s) separate from

the text, references should be listed in numerical order. When an article has more than three authors only the names of the first three

authors should be given followed by „et al.‟ The issue number should be omitted if there is continuous pagination throughout a

volume. Names and initials of authors of unpublished work should be given in the text as „unpublished results‟ and not included in

the References. Titles of journals should appear in their abbreviated form using the NCBI LinkOut page

http://www.ncbi.nlm.nih.gov/projects/linkout/journals/jourlists.fcgi?typeid=1&type=journals&operation=Show References to books

and monographs should include the town of publication and the number of the edition to which reference is made. Thus:

1. Setchell KD, Faughnan MS, Avades T et al. (2003) Comparing the pharmacokinetics of daidzein and genistein with the use of

13C-labeled tracers in premenopausal women. Am J Clin Nutr 77, 411–419.

2. Barker DJ, Winter PD, Osmond C et al. (1989) Weight in infancy and death from ischaemic heart disease. Lancet ii, 577–580.

3. Forchielli ML & Walker WA (2005) The role of gut-associated lymphoid tissues and mucosal defence. Br J Nutr 93, Suppl. 1,

S41–S48.

4. Bradbury J, Thomason JM, Jepson NJA et al. (2003) A nutrition education intervention to increase the fruit and vegetable intake

of denture wearers. Proc Nutr Soc 62, 86A.

5. Frühbeck G, Gómez-Ambrosi J, Muruzabal FJ et al. (2001) The adipocyte: a model for integration of endocrine and metabolic

signaling in energy metabolism regulation. Am J Physiol Endocrinol Metab 280, E827–E847.

6. Han KK, Soares JM Jr, Haidar MA et al. (2002) Benefits of soy isoflavone therapeutic regimen on menopausal symptoms. Obst

Gynecol 99, 389–394.

7. Uhl M, Kassie F, Rabot S et al. (2004) Effect of common Brassica vegetables (Brussels sprouts and red cabbage) on the

development of preneoplastic lesions induced by 2-amino-3-methylimidazo[4,5-f]quinoline (IQ) in liver and colon of Fischer 344

rats. J Chromatogr 802B, 225–230.

8. Hall WL, Vafeiadou K, Hallund J et al. (2005) Soy isoflavone enriched foods and inflammatory biomarkers of cardiovascular risk

in postmenopausal women: interactions with genotype and equol production. Am J Clin Nutr (In the Press).

9. Skurk T, Herder C, Kraft I et al. (2004) Production and release of macrophage migration inhibitory factor from human adipocytes.

Endocrinology (Epublication ahead of print version).

10. Skurk T, Herder C, Kraft I et al. (2005) Production and release of macrophage migration inhibitory factor from human

adipocytes. Endocrinology 146, 1006–1011; Epublication 2 December 2004.

11. Bradbury J (2002) Dietary intervention in edentulous patients. PhD Thesis, University of Newcastle.

12. Ailhaud G & Hauner H (2004) Development of white adipose tissue. In Handbook of Obesity. Etiology and Pathophysiology, 2nd

ed., pp. 481–514 [GA Bray and C Bouchard, editors]. New York: Marcel Dekker.

13. Bruinsma J (editor) (2003) World Agriculture towards 2015/2030: An FAO Perspective. London: Earthscan Publications.

14. Griinari JM & Bauman DE (1999) Biosynthesis of conjugated linoleic acid and its incorporation into meat and milk in ruminants.

In Advances in Conjugated Linoleic Acid Research, vol. 1, pp. 180–200 [MP Yurawecz, MM Mossoba, JKG Kramer, MW Pariza

and GJ Nelson, editors]. Champaign, IL: AOCS Press.

15. Henderson L, Gregory J, Irving K et al. (2004) National Diet and Nutrition Survey: Adults Aged 19 to 64 Years. vol. 2: Energy,

Protein, Fat and Carbohydrate Intake. London: The Stationery Office.

16. International Agency for Research on Cancer (2004) Cruciferous Vegetables, Isothiocyanates and Indoles. IARC Handbooks of

Cancer Prevention no. 9 [H Vainio and F Bianchini, editors]. Lyon, France: IARC Press.

17. Linder MC (1996) Copper. In Present Knowledge in Nutrition, 7th ed., pp. 307–319 [EE Zeigler and LJ Filer Jr, editors].

Washington, DC: ILSI Press.

18. World Health Organization (2003) Diet, Nutrition and the Prevention of Chronic Diseases. Joint WHO/FAO Expert Consultation.

WHO Technical Report Series no. 916. Geneva: WHO.

19. Keiding L (1997) Astma, Allergi og Anden Overfølsomhed i Danmark – Og Udviklingen 1987–199I (Asthma, Allergy and Other

Hypersensitivities in Denmark, 1987–1991). Copenhagen, Denmark: Dansk Institut for Klinisk Epidemiologi.

References to material available on websites should include the full Internet address, and the date of the version cited. Thus:

20. Department of Health (1997) Committee on Toxicity of Chemicals in Food Consumer Products and the Environment. Statement

on vitamin B6 (pyridoxine) toxicity. http://www.open.gov.uk/doh/hef/B6.htm

21. Kramer MS & Kakuma R (2002) The Optimal Duration of Exclusive Breastfeeding: A Systematic Review. Rome: WHO;

available at http://www.who.int/nut/documents/optimal_duration_of_exc_bfeeding_review_eng.pd

22. Hooper L, Thompson RL, Harrison RA et al. (2004) Omega 3 fatty acids for prevention and treatment of cardiovascular disease.

Cochrane Database of Systematic Reviews, issue 4, CD003177.

http://www.mrw.interscience.wiley.com/cochrane/clsysrev/articles/CD003177/frame.html

23. Nationmaster (2005) HIV AIDS – Adult prevalence rate. http://www.nationmaster.com/graph-T/hea_hiv_aid_adu_pre_rat

(accessed June 2005).

Mathematical modelling of nutritional processes. Papers in which mathematical modelling of nutritional processes forms the

principal element will be considered for publication provided: (a) they are based on sound biological and mathematical principles; (b)

they advance nutritional concepts or identify new avenues likely to lead to such advances; (c) assumptions used in their construction

are fully described and supported by appropriate argument; (d) they are described in such a way that the nutritional purpose is clearly

apparent; (e) the contribution of the model to the design of future experimentation is clearly defined.

Units. Results should be presented in metric units according to the International System of Units (see Quantities, Units, and Symbols

(1971) London: The Royal Society, and Metric Units, Conversion Factors and Nomenclature in Nutritional and Food Sciences (1972)

London: The Royal Society – as reproduced in Proceedings of the Nutrition Society (1972) 31, 239–247). SI units should be used

throughout the paper. The author will be asked to convert any values that are given in any other form. The only exception is where

there is a unique way of expressing a particular variable that is in widespread use. Energy values must be given in Joules (MJ or kJ)

using the conversion factor 1 kcal = 4·184 kJ. If required by the author, the value in kcal can be given afterwards in parentheses.

Temperature is given in degrees Celsius (ºC). Vitamins should be given as mg or μg, not as IU.

For substances of known molecular mass (Da) or relative molecular mass, e.g. glucose, urea, Ca, Na, Fe, K, P, values should be

expressed as mol/l; for substances of indeterminate molecular mass (Da) or relative molecular mass, e.g. phospholipids, proteins, and

for trace elements, e.g. Cu, Zn, then g/l should be used.

Time. The 24 h clock should be used, e.g. 15.00 hours.

Units are: year, month, week, d, h, min, s, kg, g, mg, μg, litre, ml, μl, fl. To avoid misunderstandings, the word litre should be

used in full, except in terms like g/l. Radioactivity should be given in becquerels (Bq or GBq) not in Ci. 1 MBq = 27·03 μCi (1Bq = 1

disintegration/s).

Statistical treatment of results. Data from individual replicates should not be given for large experiments, but may be given for

small studies. The methods of statistical analysis used should be described, and references to statistical analysis packages included in

the text, thus: Statistical Analysis Systems statistical software package version 6.11 (SAS Institute, Cary, NC, USA). Information

such as analysis of variance tables should be given in the paper only if they are relevant to the discussion. A statement of the number

of replicates, their average value and some appropriate measure of variability is usually sufficient.

Comparisons between means can be made by using either confidence intervals (CI) or significance tests. The most appropriate of

such measures is usually the standard error of a difference between means (SED), or the standard errors of the means (SE or SEM)

when these vary between means. The standard deviation (SD) is more useful only when there is specific interest in the variability of

individual values. The degrees of freedom (df) associated with SED, SEM or SD should also be stated. The number of decimal places

quoted should be sufficient but not excessive. Note that pH is an exponential number, as are the log(10) values often quoted for

microbial numbers. Statistics should be carried out on the scalar rather than the exponential values.

If comparisons between means are made using CI, the format for presentation is, e.g. „difference between means 0·73 (95 % CI

0·314, 1·36) g‟. If significance tests are used, a statement that the difference between the means for two groups of values is (or is not)

statistically significant should include the level of significance attained, preferably as an explicit P value (e.g. P=0·016 or P=0·32)

rather than as a range (e.g. P<0·05 or P>0·05}. It should be stated whether the significance levels quoted are one-sided or two-sided.

Where a multiple comparison procedure is used, a description or explicit reference should be given. Where appropriate, a superscript

notation may be used in tables to denote levels of significance; similar superscripts should denote lack of a significant difference.

Where the method of analysis is unusual, or if the experimental design is at all complex, further details (e.g. experimental plan,

raw data, confirmation of assumptions, analysis of variance tables, etc.) should be included.

Figures. In curves presenting experimental results the determined points should be clearly shown, the symbols used being, in order

of preference, ○, ●, Δ, ▲, □, ■, ×, + . Curves and symbols should not extend beyond the experimental points. Scale-marks on the

axes

should be on the inner side of each axis and should extend beyond the last experimental point. Ensure that lines and symbols used in

graphs and shading used in histograms are large enough to be easily identified when the figure is reduced to fit the printed page.

Figures and diagrams can be prepared using most applications but please do not use the following: cdx, chm, jnb or PDF. All

figures should be numbered and legends should be provided. Each figure, with its legend, should be comprehensible without

reference to the text and should include definitions of abbreviations. Latin names for unusual species should be included unless they

have already been specified in the text. Each figure will be positioned near the point in the text at which it is first introduced unless

instructed otherwise.

Note that authors will be charged 350 GBP for the publication of colour figures. Authors from countries entitled to free journal

access through HINARI will be exempt from these charges.

Refer to a recent copy of the journal for examples of figures.

Plates. The British Journal of Nutrition will now also consider the inclusion of illustrations and photomicrographs. The size of

photomicrographs may have to be altered in printing; in order to avoid mistakes the magnification should be shown by scale on the

photograph itself. The scale with the appropriate unit together with any lettering should be drawn by the author, preferably using

appropriate software.

Tables. Tables should carry headings describing their content and should be comprehensible without reference to the text. Tables

should not be subdivided by ruled lines. The dimensions of the values, e.g. mg/kg, should be given at the top of each column.

Separate columns should be used for measures of variance (SD, SE etc.), the ± sign should not be used. The number of decimal places

used should be standardized; for whole numbers 1·0, 2·0 etc. should be used. Shortened forms of the words weight (wt) height (ht)

and experiment (Expt) may be used to save space in tables, but only Expt (when referring to a specified experiment, e.g. Expt 1) is

acceptable in the heading.

Footnotes are given in the following order: (1) abbreviations, (2) superscript letters, (3) symbols. Abbreviations are given in the

format: RS, resistant starch. Abbreviations appear in the footnote in the order that they appear in the table (reading from left to right

across the table, then down each column). Abbreviations in tables must be defined in footnotes. Symbols for footnotes should be used

in the sequence: *†‡§||¶, then ** etc. (omit * or †, or both, from the sequence if they are used to indicate levels of significance).

For indicating statistical significance, superscript letters or symbols may be used. Superscript letters are useful where

comparisons are within a row or column and the level of significance is uniform, e.g. „a,b,cMean values within a column with unlike

superscript letters were significantly different (P<0·05)‟. Symbols are useful for indicating significant differences between rows or

columns, especially where different levels of significance are found, e.g. „Mean values were significantly different from those of the

control group: *P<0·05, **P<0·01, ***P<0·001‟. The symbols used for P values in the tables must be consistent.

Tables should be placed at the end of the text. Each table will be positioned near the point in the text at which it is first introduced

unless instructed otherwise.

Please refer to a recent copy of the journal for examples of tables.

Chemical formulas. These should be written as far as possible on a single horizontal line. With inorganic substances, formulas may

be used from first mention. With salts, it must be stated whether or not the anhydrous material is used, e.g. anhydrous CuSO4, or

which of the different crystalline forms is meant, e.g. CuSO4.5H2O, CuSO4.H2O.

Descriptions of solutions, compositions and concentrations. Solutions of common acids, bases and salts should be defined in

terms of molarity (M), e.g. 0·1 M-NaH2PO4. Compositions expressed as mass per unit mass (w/w) should have values expressed as ng,

μg, mg or g per kg; similarly for concentrations expressed as mass per unit volume (w/v), the denominator being the litre. If

concentrations or compositions are expressed as a percentage, the basis for the composition should be specified (e.g. % (w/w) or %

(w/v) etc.). The common measurements used in nutritional studies, e.g. digestibility, biological value and net protein utilization,

should be expressed as decimals rather than as percentages, so that amounts of available nutrients can be obtained from analytical

results by direct multiplication. See Metric Units, Conversion Factors and Nomenclature in Nutritional and Food Sciences. London:

The Royal Society, 1972 (para. 8).

Cell lines. The Journal expects authors to deposit cell lines (including microbial strains) used in any study to be published in publicly

accessible culture collections, for example, the European Collection of Cell Cultures (ECACC) or the American Type Culture

Collection (ATCC) and to refer to the collection and line or strain numbers in the text (e.g. ATCC 53103). Since the authenticity of

subcultures of culture collection specimens that are distributed by individuals cannot be ensured, authors should indicate laboratory

line or strain designations and donor sources as well as original culture collection identification numbers.

Nomenclature of vitamins. Most of the names for vitamins and related compounds that are accepted by the Editors are those

recommended by the IUNS Committee on Nomenclature. See Nutrition Abstracts and Reviews (1978) 48A, 831–835.

Acceptable name Other names*

Vitamin A

Retinol Vitamin A1

Retinaldehyde, retinal Retinene

Retinoic acid (all-trans or 13-cis) Vitamin A1 acid

3-Dehydroretinol Vitamin A2

Vitamin D

Ergocalciferol, ercalciol Vitamin D2 calciferol

Cholecalciferol, calciol Vitamin D3

Vitamin E

α-, β- and γ-tocopherols plus

tocotrienols

Vitamin K

Phylloquinone Vitamin K1

Menaquinone-n (MK-n)† Vitamin K2

Menadione Vitamin K3,

menaquinone,

menaphthone

Vitamin B1

Thiamin Aneurin(e), thiamine

Vitamin B2

Riboflavin Vitamin G, riboflavine,

lactoflavin

Niacin

Nicotinamide Vitamin PP

Nicotinic acid

Folic Acid

Pteroyl(mono)glutamic acid Folacin, vitamin Bc or M

Vitamin B6

Pyridoxine Pyridoxol

Pyridoxal

Pyridoxamine

Vitamin B12

Cyanocobalamin

Hydroxocobalamin Vitamin B12a or B12b

Aquocobalamin

Methylcobalamin

Adenosylcobalamin

Inositol

Myo-inositol Meso-inositol

Choline

Pantothenic acid

Biotin Vitamin H

Vitamin C

Ascorbic acid

Dehydroascorbic acid

*Including some names that are still in use elsewhere, but are not used by the British Journal of Nutrition.

†Details of the nomenclature for these and other naturally-occurring quinones should follow the Tentative Rules of the IUPACIUB

Commission on Biochemical Nomenclature (see European Journal of Biochemistry (1975) 53, 15–18).

Generic descriptors. The terms vitamin A, vitamin C and vitamin D may still be used where appropriate, for example in

phrases such as „vitamin A deficiency‟, „vitamin D activity‟.

Vitamin E. The term vitamin E should be used as the descriptor for all tocol and tocotrienol derivatives exhibiting qualitatively

the biological activity of α-tocopherol. The term tocopherols should be used as the generic descriptor for all methyl tocols. Thus, the

term tocopherol is not synonymous with the term vitamin E.

Vitamin K. The term vitamin K should be used as the generic descriptor for 2-methyl-1,4-naphthoquinone (menaphthone) and

all derivatives exhibiting qualitatively the biological activity of phylloquinone (phytylmenaquinone).

Niacin. The term niacin should be used as the generic descriptor for pyridine 3-carboxylic acid and derivatives exhibiting

qualitatively the biological activity of nicotinamide.

Vitamin B6. The term vitamin B6 should be used as the generic descriptor for all 2-methylpyridine derivatives exhibiting

qualitatively the biological activity of pyridoxine.

Folate. Due to the wide range of C-substituted, unsubstituted, oxidized, reduced and mono- or polyglutamyl side-chain

derivatives of pteroylmonoglutamic acid that exist in nature, it is not possible to provide a complete list. Authors are encouraged to

use either the generic name or the correct scientific name(s) of the derivative(s), as appropriate for each circumstance.

Vitamin B12. The term vitamin B12 should be used as the generic descriptor for all corrinoids exhibiting qualitatively the

biological activity of cyanocobalamin. The term corrinoids should be used as the generic descriptor for all compounds containing

the corrin nucleus and thus chemically related to cyanocobalamin. The term corrinoid is not synonymous with the term vitamin B12.

Vitamin C. The terms ascorbic acid and dehydroascorbic acid will normally be taken as referring to the naturally-occurring Lforms.

If the subject matter includes other optical isomers, authors are encouraged to include the L- or D- prefixes, as appropriate. The

same is true for all those vitamins which can exist in both natural and alternative isomeric forms.

Amounts of vitamins and summation. Weight units are acceptable for the amounts of vitamins in foods and diets. For

concentrations in biological tissues, SI units should be used; however, the authors may, if they wish, also include other units, such as

weights or international units, in parentheses.

See Metric Units, Conversion Factors and Nomenclature in Nutritional and Food Sciences (1972) paras 8 and 14–20. London:

The Royal Society.

Nomenclature of fatty acids and lipids. In the description of results obtained for the analysis of fatty acids by conventional GLC,

the shorthand designation proposed by Farquhar JW, Insull W, Rosen P, Stoffel W & Ahrens EH (Nutrition Reviews (1959), 17,

Suppl.) for individual fatty acids should be used in the text, tables and figures. Thus, 18 : 1 should be used to represent a fatty acid

with eighteen carbon atoms and one double bond; if the position and configuration of the double bond is unknown. The shorthand

designation should also be used in the abstract. If the positions and configurations of the double bonds are known, and these are

important to the discussion, then a fatty acid such as linoleic acid may be referred to as cis-9,cis-12-18 : 2 (positions of double bonds

related to the carboxyl carbon atom 1). However, to illustrate the metabolic relationship between different unsaturated fatty acid

families, it is sometimes more helpful to number the double bonds in relation to the terminal methyl carbon atom, n. The preferred

nomenclature is then: 18 : 3n-3 and 18 : 3n-6 for α-linolenic and γ-linolenic acids respectively; 18 : 2n-6 and 20 : 4n-6 for linoleic

and arachidonic acids respectively and 18 : 1n-9 for oleic acid. Positional isomers such as α- and γ-linolenic acid should always be

clearly distinguished. It is assumed that the double bonds are methylene-interrupted and are of the cis-configuration (see Holman RT

in Progress in the Chemistry of Fats and Other Lipids (1966) vol. 9, part 1, p. 3. Oxford: Pergamon Press). Groups of fatty acids that

have a common chain length but vary in their double bond content or double bond position should be referred to, for example, as C20

fatty acids or C20 PUFA. The modern nomenclature for glycerol esters should be used, i.e. triacylglycerol, diacylglycerol,

monoacylglycerol not triglyceride, diglyceride, monoglyceride. The form of fatty acids used in diets should be clearly stated, i.e.

whether ethyl esters, natural or refined fats or oils. The composition of the fatty acids in the dietary fat and tissue fats should be stated

clearly, expressed as mol/100 mol or g/100 g total fatty acids.

Nomenclature of micro-organisms. The correct name of the organism, conforming with international rules of nomenclature, should

be used: if desired, synonyms may be added in parentheses when the name is first mentioned. Names of bacteria should conform to

the current Bacteriological Code and the opinions issued by the International Committee on Systematic Bacteriology. Names of algae

and fungi must conform to the current International Code of Botanical Nomenclature. Names of protozoa should conform to the

current International Code of Zoological Nomenclature.

Nomenclature of plants. For plant species where a common name is used that may not be universally intelligible, the Latin name in

italics should follow the first mention of the common name. The cultivar should be given where appropriate.

Other nomenclature, symbols and abbreviations. Authors should consult recent issues of the British Journal of Nutrition for

guidance. The IUPAC rules on chemical nomenclature should be followed, and the Recommendations of the IUPAC-IUB

Commission on Biochemical Nomenclature (see Biochemical Journal (1978) 169, 11–14). The symbols and abbreviations, other than

units, are essentially those listed in British Standard 5775 (1979–1982), Specifications for Quantities, Units and Symbols, parts 0–13.

Day should be abbreviated to d, for example 7 d, except for „each day‟, „7th day‟ and „day 1‟.

Elements and simple chemicals (e.g. Fe and CO2) can be referred to by their chemical symbol (with the exception of arsenic and

iodine, which should be written in full) or formula from the first mention in the text; the title, text and table headings, and figure

legends can be taken as exceptions,. Well-known abbreviations for chemical substances may be used without explanation, thus: RNA

for ribonucleic acid and DNA for deoxyribonucleic acid. Other substances that are mentioned frequently (five or more times) may

also be abbreviated, the abbreviation being placed in parentheses at the first mention, thus: lipoprotein lipase (LPL), after that, LPL,

and an alphabetical list of abbreviations used should be included. Only accepted abbreviations may be used in the title and text

headings. If an author‟s initials are mentioned in the text, they should be distinguished from other abbreviations by the use of stops,

e.g. „one of us (P. J. H.)…‟. For UK counties the official names given in the Concise Oxford Dictionary (1995) should be used and

for states of the USA two-letter abbreviations should be used, e.g. MA (not Mass.) and IL (not Ill.). Terms such as „bioavailability‟ or

„available‟ may be used providing that the use of the term is adequately defined.

Spectrophotometric terms and symbols are those proposed in IUPAC Manual of Symbols and Terminology for Physicochemical

Quantities and Units (1979) London: Butterworths. The attention of authors is particularly drawn to the following symbols: m (milli,

10 3), μ (micro, 10 6), n (nano, 10 9) and p (pico, 10 12). Note also that ml (millilitre) should be used instead of cc, μm (micrometre)

instead of μ (micron) and μg (microgram) instead of γ.

Numbers. Numerals should be used with units, for example, 10 g, 7 d, 4 years (except when beginning a sentence, thus: „Four

years ago...‟); otherwise, words (except when 100 or more), thus: one man, ten ewes, ninety-nine flasks, three times (but with

decimal, 2·5 times), 100 patients, 120 cows, 136 samples.

Abbreviations. The following abbreviations are accepted without definition by the British Journal of Nutrition:

ADP (GDP) adenosine (guanosine) 5‟-disphosphate

AIDS acquired immune deficiency syndrome

AMP (GMP) adenosine (guanosine) 5‟-monophosphate

ANOVA analysis of variance

apo apolipoprotein

ATP (GTP) adenosine (guanosine) 5‟-triphosphate

BMI body mass index

BMR basal metabolic rate

bp base pair

BSE bovine spongiform encephalopathy

CHD coronary heart disease

CI confidence interval

CJD Creutzfeldt-Jacob disease

CoA and acyl-CoA co-enzyme A and its acyl derivatives

CV coefficient of variation

CVD cardiovascular disease

Df degrees of freedom

DHA docosahexaenoic acid

DM dry matter

DNA deoxyribonucleic acid

dpm disintegrations per minute

EDTA ethylenediaminetetra-acetic acid

ELISA enzyme-linked immunosorbent assay

EPA eicosapentaenoic acid

Expt experiment (for specified experiment, e.g. Expt 1)

FAD flavin-adenine dinucleotide

FAO Food and Agriculture Organization (except when used as an author)

FFQ food-frequency questionnaire

FMN flavin mononucleotide

GC gas chromatography

GLC gas–liquid chromatography

GLUT glucose transporter

GM genetically modified

Hb haemoglobin

HDL high-density lipoprotein

HEPES 4-(2-hydroxyethyl)-1-piperazine-ethanesulfonic acid

HIV human immunodeficiency virus

HPLC high-performance liquid chromatography

Ig immunoglobulin

IHD ischaemic heart disease

IL interleukin

IR infra red

kb kilobases

Km Michaelis constant

LDL low-density lipoprotein

MHC major histocompatibility complex

MRI magnetic resonance imaging

MS mass spectrometry

MUFA monounsaturated fatty acids

NAD+, NADH oxidized and reduced nicotinamide-adenine dinucleotide

NADP+, NADPH oxidized and reduced nicotinamide-adenine dinucleotide phosphate

NEFA non-esterified fatty acids

NF-κB nuclear factor kappa B

NMR nuclear magnetic resonance

NS not significant

NSP non-starch polysaccharide

OR odds ratio

PAGE polyacrylamide gel electrophoresis

PBS phosphate-buffered saline

PCR polymerase chain reaction

PG prostaglandin

PPAR peroxisome proliferator-activated receptor

PUFA polyunsaturated fatty acids

RDA recommended dietary allowance

RER respiratory exchange ratio

RIA radioimmunoassay

RMR resting metabolic rate

RNA, mRNA etc. ribonucleic acid, messenger RNA etc.

rpm revolutions per minute

RT reverse transcriptase

SCFA short-chain fatty acids

SDS sodium dodecyl sulphate

SED standard error of the difference between means

SFA saturated fatty acids

TAG triacylglycerol

TCA trichloroacetic acid

TLC thin-layer chromatography

TNF tumour necrosis factor

UN United Nations (except when used as an author)

UNICEF United Nations International Children‟s Emergency Fund

UV ultra violet

VLDL very-low-density lipoprotein

VO2 O2 consumption

VO2max maximum O2 consumption

WHO World Health Organization (except when used as an author)

Use of three-letter versions of amino acids in tables: Leu, His, etc.

CTP, UTP, GTP, ITP, as we already use ATP, AMP etc.

Disallowed words and phrases. The following are disallowed by the British Journal of Nutrition:

deuterium or tritium (use 2H and 3H)

c.a. or around (use approximately or about)

canola (use rapeseed)

ether (use diethyl ether)

free fatty acids (use NEFA)

isocalorific/calorie (use isoenergetic/energy)

quantitate (use quantify)

unpublished data or observations (use unpublished results)

Ethics of human experimentation. The notice of contributors is drawn to the guidelines in the World Medical Association (2000)

Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects, with notes of clarification of 2002 and

2004 (http://www.wma.net/e/policy/b3.htm), the Guidelines on the Practice of Ethics Committees Involved in Medical Research

Involving Human Subjects (3rd ed., 1996; London: The Royal College of Physicians) and the Guidelines for the Ethical Conduct of

Medical Research Involving Children, revised in 2000 by the Royal College of Paediatrics and Child Health: Ethics Advisory

Committee (Arch Dis Child (2000) 82, 177–182). A paper describing any experimental work on human subjects must include the

following statement: “This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all

procedures involving human subjects/patients were approved by the [insert name of the ethics committee; a specific ethics number

may be inserted following this if the authors wish]. Written [or Verbal] informed consent was obtained from all subjects/patients.

[Where verbal consent was obtained this must be followed by a statement such as: Verbal consent was witnessed and formally

recorded].”

Ethics and care of vertebrate animals used in scientific investigations. The Editors will not accept papers reporting work carried

out using inhumane procedures. When reporting on experiments involving the use of vertebrate animals, authors must state whether

institutional and national guidelines for the care and use of animals were followed and that all experimental procedures involving

animals were approved by the [insert name of the ethics committee or other approving body; the authors could insert a specific

ethics/approval number following this if they wish].

Disclosure of financial support and other relevant interests. The source of funding should be identified in the acknowledgement

section of the manuscript. All potential conflicts of interest, or financial interests of the author in a product or company that is

relevant to the article, should be declared.

Proofs. PDF proofs are sent to authors in order that they make sure that the paper has been correctly set up in type. Excessive

alterations involving changes other than typesetting errors may have to be disallowed or made at the author's expense. All corrections

should be made in ink in the margins: marks made in the text should be only those indicating the place to which the corrections refer.

Corrected proofs should be returned within 3 days either by Express mail or email to:

Emma Pearce

Production Editor

Journals Department

Cambridge University Press

The Edinburgh Building

Shaftesbury Road

Cambridge CB2 2RU

UK

Telephone: +44 1223 325032

Fax: +44 1223 325802

Email: bjnproduction@cambridge.org

If corrected proofs are not received from authors within 7 days the paper may be published as it stands.

Offprints. A copy of the issue and a PDF file of the paper will be supplied free of charge to the corresponding author of each paper

or short communication, and offprints may be ordered on the order form sent with the proofs.

SUBMISSION PROCESS

The British Journal of Nutrition now operates an on-line submission and reviewing system (eJournalPress). Authors should

submit to the following address: http://bjn.msubmit.net/. If any difficulties are encountered please contact the Publications Office

immediately.

The manuscript submission process is broken into a series of four screens that gather detailed information about your manuscript and

allow you to upload the appropriate text and figure/table files. The sequence of screens is as follows:

1. A form requesting author details, manuscript title, abstract, and associated information and the file quantities. Although there

is the option of saving your information and returning to complete your submission at a later date we strongly advise you to

submit your paper in one session if possible.

2. A screen asking for the actual file locations (via an open file dialogue). After completing this screen, your files will be

uploaded to our server.

3. A completion screen that will provide you with a specific manuscript number for your manuscript. You may be asked to

select the order in which your uploaded files should be presented.

4. An approval screen that will allow you to verify that your manuscript has been uploaded and converted to PDF correctly.

Each converted file must be approved individually to complete your online submission. If the conversion is not correct, you

can replace or delete your manuscript files as necessary. After you have reviewed the converted files, you will need to click

on "Approve Manuscript". This link will have a red arrow next to it.

Throughout the system, red arrows reflect pending action items that you should address.

Before submitting a manuscript, please gather the following details for all authors:

• Title, First and Last Names

• Full Postal Address for Corresponding Author only

• Institutions

• Country

• Work Fax Number for Corresponding Author only (including international dialling code)

• Email addresses

In addition we require full manuscript details:

• Covering Letter

• Title (you may copy and paste this from your manuscript)

• Abstract (you may copy and paste this from your manuscript)

• Manuscript files in Word, WordPerfect, or RTF format.

• Ideally manuscript files should have the tables/figures given at the end of the article.

• For illustrations, preferred software packages are Adobe Illustrator, Adobe Photoshop, Aldus Freehand, Chemdraw or

CorelDraw. Preferred formats are TIFF or JPEG, if a TIFF file is not possible save as an EPS or a windows metafile.

Figures should be submitted as separate files, not as part of the main body of the manuscript.

Please provide contact details for up to four potential Referees (email addresses and institutions).

For further information, please contact the Publications Office:

Tel: +44 (0)20 7605 6555

Fax: +44 (0) 20 7602 1756

Email: edoffice@nutsoc.org.uk

ANEXO E – COMPROVANTE DE SUBMISSÃO DE ARTIGO

Cópia do comprovante de submissão do artigo intitulado: Association of DRD2

TaqIA and -141C InsDel polymorphisms with food intake and anthropometric

data in Brazilian children à Revista British Journal of Nutrition.

Livros Grátis( http://www.livrosgratis.com.br )

Milhares de Livros para Download: Baixar livros de AdministraçãoBaixar livros de AgronomiaBaixar livros de ArquiteturaBaixar livros de ArtesBaixar livros de AstronomiaBaixar livros de Biologia GeralBaixar livros de Ciência da ComputaçãoBaixar livros de Ciência da InformaçãoBaixar livros de Ciência PolíticaBaixar livros de Ciências da SaúdeBaixar livros de ComunicaçãoBaixar livros do Conselho Nacional de Educação - CNEBaixar livros de Defesa civilBaixar livros de DireitoBaixar livros de Direitos humanosBaixar livros de EconomiaBaixar livros de Economia DomésticaBaixar livros de EducaçãoBaixar livros de Educação - TrânsitoBaixar livros de Educação FísicaBaixar livros de Engenharia AeroespacialBaixar livros de FarmáciaBaixar livros de FilosofiaBaixar livros de FísicaBaixar livros de GeociênciasBaixar livros de GeografiaBaixar livros de HistóriaBaixar livros de Línguas

Baixar livros de LiteraturaBaixar livros de Literatura de CordelBaixar livros de Literatura InfantilBaixar livros de MatemáticaBaixar livros de MedicinaBaixar livros de Medicina VeterináriaBaixar livros de Meio AmbienteBaixar livros de MeteorologiaBaixar Monografias e TCCBaixar livros MultidisciplinarBaixar livros de MúsicaBaixar livros de PsicologiaBaixar livros de QuímicaBaixar livros de Saúde ColetivaBaixar livros de Serviço SocialBaixar livros de SociologiaBaixar livros de TeologiaBaixar livros de TrabalhoBaixar livros de Turismo